Using Information from Prior Runs to Improve Automated Tuning Systems
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Proceedings of the 2006 ACM/IEEE conference on Supercomputing
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ASIAN'05 Proceedings of the 10th Asian Computing Science conference on Advances in computer science: data management on the web
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International Journal of High Performance Computing Applications
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Active Harmony provides a way to automate performance tuning. In this paper, we apply the Active Harmony system to improve the performance of a cluster-based web service system. The performance improvement cannot easily be achieved by tuning individual components for such a system. The experimental results show that there is no single configuration for the system that performs well for all kinds of workloads. By tuning the parameters, Active Harmony helps the system adapt to different workloads and improve the performance up to 16%. For scalability, we demonstrate how to reduce the time when tuning a large system with many tunable parameters. Finally an algorithm is proposed to automatically adjust the structure of cluster-based web systems, and the system throughput is improved up to 70% using this technique.