COLAB: a collaborative multi-factor scheduler for asymmetric multicore processors

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

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

8 Citations (Scopus)


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 asymmetry-aware 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 publicationProceedings of the 18th ACM/IEEE International Symposium on Code Generation and Optimization (GCO 2020)
EditorsJason Mars, Lingjia Tang, Jingling Xue, Peng Wu
Place of PublicationNew York
ISBN (Print)9781450370479
Publication statusPublished - 22 Feb 2020
EventInternational Symposium on Code Generation and Optimization (CGO 2020) - San Diego, United States
Duration: 22 Feb 202026 Feb 2020

Publication series

NameInternational Symposium on Code Generation and Optimization
ISSN (Print)1931-0544
ISSN (Electronic)2643-2838


ConferenceInternational Symposium on Code Generation and Optimization (CGO 2020)
Abbreviated titleCGO 2020
Country/TerritoryUnited States
CitySan Diego
Internet address


  • Asymmetric multicore processor
  • OS scheduler
  • Multi-threaded multi-programmed workloads


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