Towards greener data centers with storage class memory: Minimizing idle power waste through coarse-grain management in fine-grain scale

Abstract

Studies have shown much of today's data centers are over-provisioned and underutilized. Over-provisioning cannot be avoided as these centers must anticipate peak load with bursty behavior. Under-utilization, to date, has also been unavoidable as systems always had to be ready for that sudden burst of requests that loom just around the corner. Previous research has pointed to turning off systems as one solution, albeit, an infeasible one due to its irresponsiveness. In this paper, we present the feasibility of using new Storage Class Memory (SCM, which encompasses specific developments such as PCM, MRAM, or FeRAM) technology to turn systems on and off with minimum overhead. This feature is used to control systems on the whole (in comparison to previous fine-grained component-wise control) in finer time scale for high responsiveness with minimized power lost to idleness. Our empirical study is done by executing real trace-like workloads on a prototype data center of embedded systems deploying FeRAM. We quantify the energy savings and performance trade-off by turning idle systems off. We show that our energy savings approach consumes energy in proportion to user requests with configurable service of quality. Based on observations made on this data center, we discuss the requirements for real deployment. Finally, our conclusion is that SCM should not be viewed as just a replacement of RAM, but rather, as a component that could potentially open a whole new field of applications. © 2010 ACM.