Memory MISER: Improving Main Memory Energy Efficiency in Servers

Abstract

Main memory power in volume and mid-range servers is growing as a fraction of total system power. The resulting energy consumption increases system cost and the heat produced reduces reliability. Emergent memory technology will provide systems with the ability to dynamically turn-on (online) and turn-off (offline) memory devices at runtime. This technology, coupled with slack in memory demand, offers the potential for significant energy savings in servers. However, to gain general acceptance in the server community, power-aware techniques must maintain performance and scale to thousands of memory devices. We propose a memory management infra-structure for energy reduction (Memory MISER) that is transparent, performance-neutral, and scalable. Memory MISER provides: 1) a prototype Linux kernel that manages memory at device granularity, and 2) a user space daemon that tracks systemic memory demand and implements energy- and performance-constrained device controller policies. Experiments on an 8-node cluster of servers show our Memory MISER conserves memory energy up to 56.8 percent with no performance degradation for scientific codes that utilized the entire cluster. For multi-user workloads, we achieved memory energy savings of up to 67.94 percent with no performance degradation. Normalizing to total system energy consumption, our power-aware memory approach reduced energy between 18.81 percent and 39.02 percent.