C L A P: Clustered L ook-Ahead Prefetching for Energy- Efficient D R AM System
Abstract: DRAM is one of the main sources of energy consumption in computer systems. Thus, reducing the energy consumption of DRAM can prolong the lifetime of battery-operated embedded/mobile systems. To this end, we propose a DRAM energy-aware prefetching scheme to increase row buffer hits and idle periods of DRAM by clustering its accesses. Although prefetching schemes have traditionally been used to improve the system performance, utilizing them for the energy conservation of DRAM has yet to be investigated. For such energy conservation, our scheme accurately predicts and clusters potential future DRAM accesses. Clustered DRAM accesses exploit a popular first-ready first-come first-serve memory request scheduling and a power-down mode of DRAM more effectively; the probability of row buffer hits and idle periods is significantly increased by our clustering scheme. As a result, large amounts of row activation and idle energy consumption, which are major energy consumption factors in modern DRAM, can be saved. Our prefetching-based memory traffic-clustering scheme was shown to reduce the power and energy consumption of DRAM and improve its performance by an average of 0.2%, 28.9%, and 15.7%, respectively, for memoryintensive programs.