QoS-Aware stochastic power management for many-cores

Anuj Pathania, Heba Khdr, Muhammad Shafique, Tulika Mitra, Jörg Henkel

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

Abstract

A many-core processor can execute hundreds of multi-threaded tasks in parallel on its 100s-1000s of processing cores. When deployed in a Quality of Service (QoS)-based system, the many-core must execute a task at a target QoS. The amount of processing required by the task for the QoS varies over the task's lifetime. Accordingly, Dynamic Voltage and Frequency Scaling (DVFS) allows the many-core to deliver precise amount of processing required to meet the task QoS guarantee while conserving power. Still, a global control is necessitated to ensure that the many-core overall does not exceed its power budget. Previously, only non-stochastic controls have been proposed for the problem of QoS-aware power budgeting in many-cores. We propose the first stochastic control for the problem, which has a computational complexity less than the non-stochastic control by a factor of O (lnn) but with equivalent performance. The proposed stochastic control can operate with 6.4x less overhead than the non-stochastic control for a 256-task workload.

Original languageEnglish (US)
Title of host publicationProceedings of the 55th Annual Design Automation Conference, DAC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781450357005
DOIs
StatePublished - Jun 24 2018
Event55th Annual Design Automation Conference, DAC 2018 - San Francisco, United States
Duration: Jun 24 2018Jun 29 2018

Publication series

NameProceedings - Design Automation Conference
VolumePart F137710
ISSN (Print)0738-100X

Other

Other55th Annual Design Automation Conference, DAC 2018
CountryUnited States
CitySan Francisco
Period6/24/186/29/18

Keywords

  • Many-Core
  • Power Budgeting
  • Probabilistic Control

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation

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