Evaluation of the field-programmable cache: performance and energy consumption

Abstract

Many authors have proposed power management techniques for general-purpose processors at the cost of degraded performance such as lower IPC or longer delay. Some proposals have focused on cache memories because they consume a significant fraction of total microprocessor power. We propose a reconfigurable and adaptive cache microarchitecture based on field-programmable technology that is intended to deliver high performance at low energy consumption. In this paper, we evaluate the performance and energy consumption of a run-time algorithm when used to manage a field-programmable L1 data cache. The adaptation strategy is based on two techniques: a learning process provides the best cache configuration for each program phase, and a recognition process detects program phase changes by using data working-set signatures to activate a low-overhead reconfiguration mechanism. Our proposals achieve performance improvement and cache energy saving at the same time. Considering a design scenario driven by performance constraints, we show that processor execution time and cache energy consumption can be reduced on average by 15.2% and 9.9% compared to a non-adaptive high-performance microarchitecture. Alternatively, when energy saving is prioritized and considering a non-adaptive energy-efficient microarchitecture as baseline, cache energy and processor execution time are reduced on average by 46.7% and 9.4% respectively. In addition to comparing to conventional microarchitectures, we show that the proposed microarchitecture achieves better performance and more cache energy reduction than other configurable caches.