Long-term workload phases: Duration predictions and applications to DVFS

Canturk Isci, Alper Buyuktosunoglu, Margaret Rose Martonosi

Research output: Contribution to journalArticle

54 Scopus citations

Abstract

Computer systems increasingly rely on adaptive dynamic management of their operations to balance power and performance goals. Such dynamic adjustments rely heavily on the system's ability to observe and predict workload behavior and system responses. The authors characterize the workload behavior of full benchmarks running on server-class systems using hardware performance counters. Based on these characterizations, they developed a set of long-term value, gradient, and duration prediction techniques that can help systems to provision resources.

Original languageEnglish (US)
Pages (from-to)39-51
Number of pages13
JournalIEEE Micro
Volume25
Issue number5
DOIs
StatePublished - Sep 1 2005

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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