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| Performance heterogeneous multicore processors (HMP for short), whichconsist of multiple cores with the same instruction set but different performance characteristics (e.g., clock speed, issue width), are of great concern for their ability to deliver higher performance per watt and area for programs with diverse architectural requirements than comparable homogeneous ones. However, such power and area efficiencies of performance heterogeneous multicore systems can only be achieved when workloads are emph{matched} with cores according to the properties of the workload and features of the core.In this paper, we propose a new metric, ASTPI (Average Stall Time per Instruction), to measure the efficiencies of threads in using fast cores. We design, implement and evaluate a new online monitoring approach called ESHMP, which is based on the metric. Our evaluation in the Linux 2.6.21 operating system shows that ESHMP delivers scalability while adapting to a wide variety of applications. Also, our experiment results show that among HMP systems in which heterogeneity-aware schedulers are adopted and there are more than one LLC (Last Level Cache), the architectures where heterogeneous cores share LLCs gain better performance than the ones where homogeneous cores share LLCs. |
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| Keywords:performance heterogeneous multicore; scheduling; algorithm; operating systems |
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