Enabling accurate power profiling of HPC applications on exascale systems

Abstract

Despite being one of the most important limiting factors on the road to exascale computing, power is not yet considered a "first-class citizen" among the system resources. As a result, there is no clear OS interface that exposes accurate resource power consumption to user-level runtimes that implement power-aware software algorithms. In this work we propose a System Monitor Interface (SMI) between the OS and the user runtime that exposes accurate, per-core power consumption. To make up for the lack of reliable per-core power sensors, we implement a proxy power sensor, based on a regression analysis of core activity, that provides per-core information. SMI effectively hides the implementation details from the user, who has the perception of reading power information from a real sensor. This allows us these proxy sensors to be replaced with real hardware sensors when the latter becomes available, without the need to modify user-level software. Using SMI and the proxy power sensors, we implement a power profiling runtime library and analyzed applications from the NPB benchmark suite and the Exascale Co-Design Centers. Our results show that accurate, per-core power information is necessary for the development of exascale system software and for comprehensively understanding the power characteristics of parallel scientific applications.