COLAB: A Collaborative Multi-factor Scheduler for Asymmetric Multicore Processors

Teng Yu, Pavlos Petoumenos, Vladimir Janjic, Hugh Leather, John Thomson

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Abstract

Increasingly prevalent asymmetric multicore processors (AMP) are necessary for delivering performance in the era of limited power budget and dark silicon. However, the software fails to use them efficiently. OS schedulers, in particular, handle asymmetry only under restricted scenarios. We have efficient symmetric schedulers, efficient asymmetric schedulers for single-threaded workloads, and efficient asymmetric schedulers for single program workloads. What we do not have is a scheduler that can handle all runtime factors affecting AMP for multi-threaded multi-programmed workloads. This paper introduces the first general purpose asymmetryaware scheduler for multi-threaded multi-programmed workloads. It estimates the performance of each thread on each type of core and identifies communication patterns and bottleneck threads. The scheduler then makes coordinated core assignment and thread selection decisions that still provide each application its fair share of the processor's time. We evaluate our approach using the GEM5 simulator on four distinct big.LITTLE configurations and 26 mixed workloads composed of PARSEC and SPLASH2 benchmarks. Compared to the state-of-the art Linux CFS and AMP-aware schedulers, we demonstrate performance gains of up to 25% and 5% to 15% on average depending on the hardware setup.

Original languageEnglish
Title of host publicationCGO 2020 - Proceedings of the 18th ACM/IEEE International Symposium on Code Generation and Optimization
Subtitle of host publicationCGO 2020
EditorsJason Mars, Lingjia Tang, Jingling Xue, Peng Wu
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Pages268-279
Number of pages12
ISBN (Electronic)9781450370479
ISBN (Print)9781450370479
DOIs
Publication statusPublished - Feb 2020
EventProceedings of the 18th ACM/IEEE International Symposium on Code Generation and Optimization: CGO'20 - San Diego, United States
Duration: 22 Feb 202026 Feb 2020
https://doi.org/10.1145/3368826.3377915

Publication series

NameCGO 2020 - Proceedings of the 18th ACM/IEEE International Symposium on Code Generation and Optimization

Conference

ConferenceProceedings of the 18th ACM/IEEE International Symposium on Code Generation and Optimization
CountryUnited States
CitySan Diego
Period22/02/2026/02/20
Internet address

Keywords

  • Computer systems organization
  • Multicore architecture
  • Real-time operating systems
  • Software and its engineering
  • Runtime environments
  • Multi-threaded Multi-programmed Workloads
  • OS Scheduler
  • Asymmetric Multicore Processor

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  • Cite this

    Yu, T., Petoumenos, P., Janjic, V., Leather, H., & Thomson, J. (2020). COLAB: A Collaborative Multi-factor Scheduler for Asymmetric Multicore Processors. In J. Mars, L. Tang, J. Xue, & P. Wu (Eds.), CGO 2020 - Proceedings of the 18th ACM/IEEE International Symposium on Code Generation and Optimization: CGO 2020 (pp. 268-279). (CGO 2020 - Proceedings of the 18th ACM/IEEE International Symposium on Code Generation and Optimization). Association for Computing Machinery. https://doi.org/10.1145/3368826.3377915