Utility-based resource management in an oversubscribed energy-constrained heterogeneous environment executing parallel applications

Dylan Machovec, Bhavesh Khemka, Nirmal Kumbhare, Sudeep Pasricha, Anthony A. Maciejewski, Howard Jay Siegel, Ali Akoglu, Gregory A. Koenig, Salim Hariri, Cihan Tunc, Michael Wright, Marcia Hilton, Rajendra Rambharos, Christopher Blandin, Farah Fargo, Ahmed Louri, Neena Imam

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The worth of completing parallel tasks is modeled using utility functions, which monotonically-decrease with time and represent the importance and urgency of a task. These functions define the utility earned by a task at the time of its completion. The performance of a computing system is measured as the total utility earned by all completed tasks over some interval of time (e.g., 24 h). We have designed, analyzed, and compared the performance of a set of heuristic techniques to maximize system performance when scheduling dynamically arriving parallel tasks onto a high performance computing (HPC) system that is oversubscribed and energy constrained. We consider six utility-aware heuristics and four existing heuristics for comparison. A new concept of temporary place-holders is compared with scheduling using permanent reservations. We also present a novel energy filtering technique that constrains the maximum energy-per-resource used by each task. We conducted a simulation study to evaluate the performance of these heuristics and techniques in multiple energy-constrained oversubscribed HPC environments. We conduct an experiment with a subset of the heuristics on a physical testbed system for one scheduling scenario. We demonstrate that our proposed utility-aware resource management heuristics are able to significantly outperform existing techniques.

Original languageEnglish (US)
Pages (from-to)48-72
Number of pages25
JournalParallel Computing
Volume83
DOIs
StatePublished - Apr 2019

Keywords

  • Energy-aware computing
  • Heterogeneous computing
  • Parallel tasks
  • Resource management heuristics
  • Scheduling
  • Utility functions

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

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