Optimal partitioning of a multicore server processor

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.