RCS: Runtime resource and core scaling for power-constrained multi-core processors

Hamid Reza Ghasemi, Nam Sung Kim

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

Abstract

Providing a sufficient voltage/frequency (V/F) scaling range is critical for effective power management. However, it has been fraught with decreasing nominal operating voltage and increasing manufacturing process variability that makes it harder to scale the minimum operating voltage (VMIN). In this paper, we first present a resource and core scaling (RCS) technique that jointly scales (i) the resources of a processor and (ii) the number of operating cores to maximize the performance of power-constrained multi-core processors. More specifically, we uniformly scale the resources that are both associated with each core (e.g., L1 caches and execution units (EUs)) and shared by all the cores (e.g., last-level cache (LLC)) as a means to compensate for lack of a V/F scaling range. Under the maximum power constraint, disabling some resources allows us to increase the number of operating cores, and vice versa. We demonstrate that the best RCS configuration for a given application can improve the geometric-mean performance by 21%. Second, we propose a runtime system that predicts the best RCS configuration for a given application and adapts the processor configuration accordingly at runtime. The runtime system only needs to examine a small fraction of runtime to predict the best RCS configuration with accuracy well over 90%, whereas the runtime overhead of prediction and adaptation is small. Finally, we propose to selectively scale the resources in RCS (dubbed sRCS) depending on application's characteristics and demonstrate that sRCS can offer 6% higher geometric-mean performance than RCS that uniformly scales the resources.

Original languageEnglish (US)
Title of host publicationPACT 2014 - Proceedings of the 23rd International Conference on Parallel Architectures and Compilation Techniques
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages251-262
Number of pages12
ISBN (Print)9781450328098
DOIs
StatePublished - Jan 1 2014
Event23rd International Conference on Parallel Architectures and Compilation Techniques, PACT 2014 - Edmonton, AB, Canada
Duration: Aug 24 2014Aug 27 2014

Publication series

NameParallel Architectures and Compilation Techniques - Conference Proceedings, PACT
ISSN (Print)1089-795X

Other

Other23rd International Conference on Parallel Architectures and Compilation Techniques, PACT 2014
CountryCanada
CityEdmonton, AB
Period8/24/148/27/14

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Keywords

  • machine learning
  • power-constrained multi-core processor
  • resource and core scaling
  • voltage/frequency scaling

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture

Cite this

Ghasemi, H. R., & Kim, N. S. (2014). RCS: Runtime resource and core scaling for power-constrained multi-core processors. In PACT 2014 - Proceedings of the 23rd International Conference on Parallel Architectures and Compilation Techniques (pp. 251-262). (Parallel Architectures and Compilation Techniques - Conference Proceedings, PACT). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1145/2628071.2628095