Sensible Energy Accounting with Abstract Metering for Multicore Systems

Abstract

Chip multicore processors (CMPs) are the preferred processing platform across different domains such as data centers, real-time systems, and mobile devices. In all those domains, energy is arguably the most expensive resource in a computing system. Accurately quantifying energy usage in a multicore environment presents a challenge as well as an opportunity for optimization. Standard metering approaches are not capable of delivering consistent results with shared resources, since the same task with the same inputs may have different energy consumption based on the mix of co-running tasks. However, it is reasonable for data-center operators to charge on the basis of estimated energy usage rather than time since energy is more correlated with their actual cost. This article introduces the concept of Sensible Energy Accounting (SEA). For a task running in a multicore system, SEA accurately estimates the energy the task would have consumed running in isolation with a given fraction of the CMP shared resources. We explain the potential benefits of SEA in different domains and describe two hardware techniques to implement it for a shared last-level cache and on-core resources in SMT processors. Moreover, with SEA, an energy-aware scheduler can find a highly efficient on-chip resource assignment, reducing by up to 39% the total processor energy for a 4-core system.