Runtime performance projection model for dynamic power management

Sang Jeong Lee, Hae Kag Lee, Pen Chung Yew

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

In this paper, a runtime performance projection model for dynamic power management is proposed. The model is built as a first-order linear equation using a linear regression model. It could be used to estimate performance impact from different p-states (voltage-frequency pairs). Workload behavior is monitored dynamically for a program region of 100M instructions using hardware performance monitoring counters (PMCs), and performance for the next region is estimated using the proposed model. For each 100M-instructions interval, the performance of all processor p-states is estimated and the lowest frequency is selected within specified performance constraints. The selected frequency is set with a low-overhead DVFS-based (dynamic voltage-frequency scaling) p-state changing mechanism for the next program region. We evaluate the performance degradation and the amount of energy saving of our dynamic power management scheme using the proposed projection model for SPEC CPU2000 benchmark on a Pentium M platform. We measure the execution time and energy consumption for 4 specified constraints - 10%, 20%, 40%, 80%, on the maximum allowed performance degradation. The result shows that our dynamic management scheme saves energy consumption by 3%, 18%, 38% and 48% with a performance degradation of 3%, 19%, 45% and 79% under 10%,20%,40% and 80% constraints, respectively.

Original languageEnglish (US)
Title of host publicationAdvances in Computer Systems Architecture - 12th Asia-Pacific Conference, ACSAC 2007, Proceedings
Pages186-197
Number of pages12
StatePublished - Dec 1 2007
Event12th Asia-Pacific Computer Systems Architecture Conference, ACSAC 2007 - Seoul, Korea, Republic of
Duration: Aug 23 2007Aug 25 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4697 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th Asia-Pacific Computer Systems Architecture Conference, ACSAC 2007
CountryKorea, Republic of
CitySeoul
Period8/23/078/25/07

Keywords

  • Dynamic power management
  • Dynamic voltage-frequency scaling
  • Performance monitoring

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