IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i7p1346-d220948.html
   My bibliography  Save this article

Energy-Efficient Thread Mapping for Heterogeneous Many-Core Systems via Dynamically Adjusting the Thread Count

Author

Listed:
  • Tao Ju

    (School of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Yan Zhang

    (School of Media Engineering, Lanzhou University of Arts and Science, Lanzhou 730000, China)

  • Xuejun Zhang

    (School of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Xiaogang Du

    (School of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Xiaoshe Dong

    (School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

Improving computing performance and reducing energy consumption are a major concern in heterogeneous many-core systems. The thread count directly influences the computing performance and energy consumption for a multithread application running on a heterogeneous many-core system. For this work, we studied the interrelation between the thread count and the performance of applications to improve total energy efficiency. A prediction model of the optimum thread count, hereafter the thread count prediction model (TCPM), was designed by using regression analysis based on the program running behaviors and heterogeneous many-core architecture feature. Subsequently, a dynamic predictive thread mapping (DPTM) framework was proposed. DPTM uses the prediction model to estimate the optimum thread count and dynamically adjusts the number of active hardware threads according to the phase changes of the running program in order to achieve the optimal energy efficiency. Experimental results show that DPTM obtains a nearly 49% improvement in performance and a 59% reduction in energy consumption on average. Moreover, DPTM introduces about 2% additional overhead compared with traditional thread mapping for PARSEC (The Princeton Application Repository for Shared-Memory Computers) benchmark programs running on an Intel MIC (Many integrated core) heterogeneous many-core system.

Suggested Citation

  • Tao Ju & Yan Zhang & Xuejun Zhang & Xiaogang Du & Xiaoshe Dong, 2019. "Energy-Efficient Thread Mapping for Heterogeneous Many-Core Systems via Dynamically Adjusting the Thread Count," Energies, MDPI, vol. 12(7), pages 1-20, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1346-:d:220948
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/7/1346/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/7/1346/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tao Ju & Xiaoshe Dong & Heng Chen & Xingjun Zhang, 2016. "DagTM: An Energy-Efficient Threads Grouping Mapping for Many-Core Systems Based on Data Affinity," Energies, MDPI, vol. 9(9), pages 1-20, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1346-:d:220948. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.