Application-Aware Power Coordination on Power Bounded NUMA Multicore Systems
Rong Ge, Pengfei Zou, Xizhou Feng · 2017
Power is a critical factor that limits the performance and scalability of modern high performance computer systems. Considering power as a first-order constraint and a scarce system resource, power-bounded computing represents a new perspective to address the power challenge in HPC. In this work we present an application-aware, multi-dimensional power allocation framework to support power-bounded parallel computing on NUMA-enabled multicore systems. This framework utilizes multiple complementary software and hardware power management mechanisms to manage power distribution among sockets, cores, and NUMA memory nodes under a total power budget. More importantly, this framework implements a hierarchical power coordination method that leverages applications' performance and power scalability to efficiently identify an ideal power distribution. We describe the design of the framework and evaluate its performance on a NUMA-enabled multicore system with 24 cores. Experimental results show that the proposed framework performs close to the oracle solution for parallel programs with various power budgets.