Combinatorial auctions for temperature-constrained resource management in manycores

Heba Khdr, Muhammad Shafique, Santiago Pagani, Andreas Herkersdorf, Jorg Henkel

Research output: Contribution to journalArticlepeer-review

Abstract

Although manycore processors have plenty of cores, not all of them may run simultaneously at full speed and even some of them might need to be power-gated in order to keep the chip within safe temperature limits. Hence, a resource management technique, that allocates cores to application aiming at maximizing the system performance, will not be able to achieve its goal without taking into account the on-chip temperature and its impact on the availability of the chip's resources. However, considering a temperature constraint by the resource management will further increase its complexity, especially in manycores, and thus implementing it in a centralized scheme might lead to a computation bottleneck and a single point of failure. To avoid such scenarios, it is inevitable to distribute the computation required by the resource management technique throughout the chip. In this article, we propose a distributed resource management technique that considers temperature as an essential factor in allocating cores to applications and determining the power states of these cores and their voltage/frequency levels, while taking into account the performance models of the applications in order to maximize the overall system performance under a temperature constraint. Our proposed technique employs, for the first time, combinatorial auctions within an agent system to achieve the targeted goal in a distributed manner. The experimental evaluations show that our proposed technique achieves significant performance improvements with an average of 41% compared to several distributed resource management techniques.

Original languageEnglish (US)
Article number8955960
Pages (from-to)1605-1620
Number of pages16
JournalIEEE Transactions on Parallel and Distributed Systems
Volume31
Issue number7
DOIs
StatePublished - Jul 1 2020

Keywords

  • Dvfs
  • Performance optimization
  • Runtime resource management
  • System-level optimization
  • Temperature-aware design

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics

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