Drowsy Instruction Caches - Leakage Power Reduction using Dynamic Voltage Scaling and Cache Sub-bank Prediction: Nam Sung Kim

Authors:

Nam Sung Kim, Krisztián Flautner, David Blaauw, Trevor Mudge
Advanced Computer Architecture Lab
The University of Michigan
1301 Beal Ave. Ann Arbor, MI 48109-2122

ARM Ltd
110 Fulbourn Road
Cambridge, UK CB1 9NJ

Abstract:

On-chip caches represent a sizeable fraction of the total power consumption of microprocessors. Although large caches can significantly improve performance, they have the potential to increase power consumption. As feature sizes shrink, the dominant component of this power loss will be leakage. In our previous work we have shown how the drowsy circuit a simple, state-preserving, low-leakage circuit that relies on voltage scaling for leakage reduction can be used to reduce the total energy consumption of data caches by more than 50%. In this paper, we extend the architectural control mechanism of the drowsy cache to reduce leakage power consumption of instruction caches without significant impact on execution time. Our results show that data and instruction caches require different control strategies for efficient execution. To enable drowsy instruction caches, we propose a technique called cache subbank prediction which is used to selectively wake up only the necessary parts of the instruction cache, while allowing most of the cache to stay in a low leakage drowsy mode. This prediction technique reduces the negative performance impact by 76% compared to the no-prediction policy. Our technique works well even with small predictor sizes and enables an 86% reduction of leakage energy in a 64K byte power budget.

Web Site:

www.eecs.umich.edu/~tnm
www.eecs.umich.edu/~kimns