SHF:Small:Collaborative Research: Application-aware Energy Modeling and Power Management for Parallel and High Performance Computing

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One of the critical challenges in scaling out current and future high performance computing (HPC) and enterprise computing systems is the requirement that their power envelope remain comparable to that of today?s systems. This project addresses this ?power wall? challenge from the system software aspect by developing application-aware methodologies of energy modeling and power management. The project optimizes system efficiency by tuning performance and energy consumption to resonate with application runtime behavior while staying below the system power envelope. The project develops user interfaces and new compiler models and runtime tuning techniques to manage the tradeoffs between performance and energy consumption. The approach enables cooperative, application-specific control of energy consumption between hardware, system software and applications. The investigations and solutions deepen understanding of application power usage and guide users to customized performance and energy consumption behavior.This collaborative project integrates the development, education, and outreach efforts of collaborating University partners and is well positioned to have a substantial impact on both the HPC research community and hardware designers and vendors. All findings are published in peer-reviewed conferences and journals while source code and results are available through a project web site. This work addresses the need for energy efficiency improvements in large-scale systems in support of high-end simulations used to design pharmaceuticals, aircraft, global warming scenarios, etc. The proposed techniques influence the design of future directions HPC and enterprise computing systems from industry and government. The project engages and trains graduate and undergraduate students, including underrepresented minority students, in the area of energy efficient computing, parallel and high performance computing, and computer architecture and systems. The open source evaluation platforms are used in teaching related coursework in graduate and undergraduate classes.