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Optimal partitioning of a multicore server processor

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Abstract

Optimal partitioning of a multicore server processor in a cloud computing environment, i.e., optimal system (virtual server) configuration for some given types of applications is considered in this paper. Such optimization is important for dynamic resource provision and on-demand server customization in a cloud computing environment for certain specific types of applications, such that the overall system performance is optimized without exceeding certain energy consumption budget. A multicore server processor is treated as a group of queueing systems with multiple servers, i.e., M/M/m queueing systems. The system performance measures are the average task response time and the average power consumption. Two core speed and power consumption models are considered, namely, the idle-speed model and the constant-speed model. Three problems are formulated and solved, namely, optimal multicore server processor partitioning, optimal multicore server processor partitioning with power constraint, and optimal power allocation. All these problems are well-defined optimization problems. It is shown that although these problems are sophisticated, they can be solved by numerical algorithms. Numerical data are demonstrated for each problem.

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Acknowledgments

The author would like to express his gratitude to five anonymous reviewers for their suggestions to improve the manuscript. A preliminary version of the paper [15] was presented on Workshop on Parallel Computing and Optimization in conjunction with the 26th IEEE International Parallel and Distributed Processing Symposium, Shanghai, China, May 21–25, 2012.

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  1. Department of Computer Science, State University of New York, New Paltz, NY, 12561, USA

    Keqin Li

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  1. Keqin Li
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Correspondence to Keqin Li.

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Li, K. Optimal partitioning of a multicore server processor. J Supercomput 71, 3744–3769 (2015). https://doi.org/10.1007/s11227-015-1463-3

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  • DOI: https://doi.org/10.1007/s11227-015-1463-3

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