A Hybrid Power-Performance Adjustment Strategy for Clustered Multi-threading Architecture

Dynamic optimization techniques such as dynamic voltage and frequency scaling (DVFS), power gating (PG) and thread migration are widely used in current multi-core processor platforms to boost performance, lower power and improve energy efficiency. To obtain the best optimization results, an important issue is to predict the performance of each thread quantitatively. In this paper, a separated and clustered performance predictor, called SCP, is proposed oriented to clustered multi-threading (CMT) processors. SCP model is implemented in AMD's FX-8320 processor and its accuracy is about 6% for SPEC CPU 2006 benchmark suite. To illustrate the application and effectiveness of SCP model furthermore, we propose PPEP-SCP model for power capping, which is a combination of SCP model and PPEP model. Compared to power capping strategy based on PPEP model, strategy based on PPEP-SCP performs better in terms of the per-formance and the difference between the actual and the target power consumption, because PPEP-SCP based strategy can per-form optimization through both DVFS and PG techniques.