Run-time power estimation in high performance microprocessors
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
The benefits of event: driven energy accounting in power-sensitive systems
EW 9 Proceedings of the 9th workshop on ACM SIGOPS European workshop: beyond the PC: new challenges for the operating system
Runtime Power Monitoring in High-End Processors: Methodology and Empirical Data
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications
IEEE Transactions on Parallel and Distributed Systems
Power-performance management on an IBM POWER7 server
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Portable, scalable, per-core power estimation for intelligent resource management
GREENCOMP '10 Proceedings of the International Conference on Green Computing
Measuring Energy and Power with PAPI
ICPPW '12 Proceedings of the 2012 41st International Conference on Parallel Processing Workshops
Hi-index | 0.00 |
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.