Energy-aware resource management for computing systems

• Published in: 2014 Seventh International Conference on Contemporary Computing (IC3) pp. 7 - 12
• Main Authors: Siegel, Howard Jay, Khemka, Bhavesh, Friese, Ryan, Pasricha, Sudeep, Maciejewski, Anthony A., Koenig, Gregory A., Powers, Sarah, Hilton, Marcia, Rambharos, Rajendra, Okonski, Gene, Poole, Steve
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2014
• Subjects: bi-objective optimization; Computational modeling; Conferences; Energy consumption; energy-aware computing; heterogeneous distributed computing; high performance computing system; Laboratories; Resource management; Sociology; Statistics
• ISBN: 1479951722; 9781479951727
• DOI: 10.1109/IC3.2014.6897139

This corresponds to the material in the invited keynote presentation by H. J. Siegel, summarizing the research in [1], [2]. We address the problem of assigning dynamically-arriving tasks to machines in a heterogeneous computing environment. These machines execute a workload composed of different tasks, where the tasks have diverse computational requirements. 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 an energy constraint. 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 technique allows system administrators to investigate the trade-offs between these conflicting goals.