Sleep-Aware Variable Partitioning for Energy-Efficient Hybrid PRAM and DRAM Main Memory

Energy consumption of memories is always a significant issue for computing systems. Recently, hybrid PRAM and DRAM memory architectures have been proposed. It combines the advantages of DRAM and PRAM, such as low leakage power in PRAM and short write latency in DRAM. However, the leakage power in DRAM is still considerable in hybrid memories. The leakage power can only be reduced by turning DRAM into sleep state. In this paper, a novel proximity concept is proposed to guide the variable partitioning to maximize the possibility of turning DRAM into sleep mode. A novel Sleep-Aware Variable Partition Algorithm (SAVPA) is then proposed with the objective of maximizing the sleep time of DRAM while satisfying the performance and endurance constraints. The experiment results show that SAVPA reduces the energy consumption by 11.25% in average (up to 15.84%) compared to the state-of-art work with simple sleep technique.