Prof. H. J. Siegel

Department of Electrical and Computer Engineering and Department of Computer Science Colorado State University

Fort Collins, Colorado, USA

H. J. Siegel has been the George T. Abell Endowed Chair Distinguished Professor of Electrical and Computer Engineering at Colorado State University (CSU) since 2001, where he is also a Professor of Computer Science. From 2002 to 2013, he was the founding Director of the CSU Information Science and Technology Center (ISTeC), a university-wide organization for enhancing CSU’s activities pertaining to the design and innovative application of computer, communication, and information systems. Before joining CSU, he was a Professor at Purdue University from 1976 to 2001. He received two B.S. degrees from the Massachusetts Institute of Technology (MIT), and the M.A., M.S.E., and Ph.D. degrees from Princeton University. He is a Fellow of the IEEE and a Fellow of the ACM. Prof. Siegel has co-authored over 400 published technical papers in the areas of parallel and distributed computing. He was a Coeditor-in-Chief of the Journal of Parallel and Distributed Computing, and was on the Editorial Boards of the IEEE Transactions on Parallel and Distributed Systems and the IEEE Transactions on Computers.

Title: Energy-Aware Resource Management for Computing Systems

Abstract: Scientists and engineers always want faster and faster computers, and in general faster computers require more energy. With rising energy costs, there is an urgent need for energy-efficient computing at many different levels. This keynote focuses on some of our group’s research on energy-aware resource management in heterogeneous computing systems. We address the problem of assigning dynamically-arriving tasks to machines in a heterogeneous computing environment that isa collection of machines with different computational capabilities and energy-usage characteristics. These machines execute a workload composed of different tasks, where the tasks have diverse computational requirements. The execution time and energy consumptionof a task on a machine is based on how the task’s computational requirements interact with the machine’s capabilities. Each task has a utility function associated with it that represents the value of completing that task, and this utility decreases the longer it takes a task to complete. The goal of our resource manager is to maximize the sum of the utilities earned by all tasks arriving in the system over a given interval of time, while satisfying a constraint on how much energy is consumed. We describe example energy-aware resource management methods to accomplish this goal, and compare their performance. We also study the bi-objective problem of maximizing system utility and minimizing the system energy consumption. This analysis techniqueallows system administrators to investigate the trade-offs between these conflicting goals. We conclude with ideas for future research.

http://www.engr.colostate.edu/~hj/