• DocumentCode
    602594
  • Title

    Application-to-core mapping policies to reduce memory system interference in multi-core systems

  • Author

    Das, Ratan ; Ausavarungnirun, Rachata ; Mutlu, Onur ; Kumar, Ajit ; Azimi, Mani

  • Author_Institution
    Univ. of Michigan, Ann Arbor, MI, USA
  • fYear
    2013
  • fDate
    23-27 Feb. 2013
  • Firstpage
    107
  • Lastpage
    118
  • Abstract
    Future many-core processors are likely to concurrently execute a large number of diverse applications. How these applications are mapped to cores largely determines the interference between these applications in critical shared hardware resources. This paper proposes new application-to-core mapping policies to improve system performance by reducing inter-application interference in the on-chip network and memory controllers. The major new ideas of our policies are to: 1) map network-latency-sensitive applications to separate parts of the network from network-bandwidth-intensive applications such that the former can make fast progress without heavy interference from the latter, 2) map those applications that benefit more from being closer to the memory controllers close to these resources. Our evaluations show that, averaged over 128 multiprogrammed workloads of 35 different benchmarks running on a 64-core system, our final application-to-core mapping policy improves system throughput by 16.7% over a state-of-the-art baseline, while also reducing system unfairness by 22.4% and average interconnect power consumption by 52.3%.
  • Keywords
    multiprocessing systems; network-on-chip; power aware computing; 64-core system; application-to-core mapping policies; application-to-core mapping policy; critical shared hardware resources; inter-application interference reduction; interconnect power consumption reduction; many-core processors; memory controllers; memory system interference reduction; multicore systems; multiprogrammed workloads; network-bandwidth-intensive applications; network-latency-sensitive applications; on-chip network; system performance improvement; Bandwidth; Clustering algorithms; Interference; Program processors; Sensitivity; System performance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computer Architecture (HPCA2013), 2013 IEEE 19th International Symposium on
  • Conference_Location
    Shenzhen
  • ISSN
    1530-0897
  • Print_ISBN
    978-1-4673-5585-8
  • Type

    conf

  • DOI
    10.1109/HPCA.2013.6522311
  • Filename
    6522311