Gregory A. Koenig

TL;DR: Extensive sensitivity analyses of the heuristics in environments with different levels of heterogeneity show that heuristic with the ability to balance both energy consumption and utility exhibit the best performance because they save energy for use by future tasks.

TL;DR: The results show the benefit of having fast heuristics that account for the importance of a task and the heterogeneity of the environment when making allocation decisions in an oversubscribed environment.

TL;DR: In this article, some of the largest supercomputing centers (SCs) in the United States are developing new relationships with their electricity service providers (ESPs), which are driven by a mutual interest to reduce energy costs and improve electrical grid reliability.

TL;DR: An analysis framework that will allow a system administrator to investigate the tradeoffs between system energy consumption and utility earned by a system (as a measure of system performance), and model these trade-offs as a bi-objective resource allocation problem.

TL;DR: This work describes the motivation and methodology of a first-of-its-kind global survey of HPC centers actively employing Energy and Power Aware Scheduling and Resource Management solutions for their production systems and presents the selection of participating sites.