• DocumentCode
    2907113
  • Title

    Power-Performance Comparison of Single-Task Driven Many-Cores

  • Author

    Keceli, Fuat ; Moreshet, Tali ; Vishkin, Uzi

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
  • fYear
    2011
  • fDate
    7-9 Dec. 2011
  • Firstpage
    348
  • Lastpage
    355
  • Abstract
    Many-cores, processors with 100s of cores, are becoming increasingly popular in general-purpose computing, yet power is a limiting factor in their performance. In this paper, we compare the power and performance of two design points in the many-core processor domain. The XMT general-purpose processor provides significant runtime advantage on irregular parallel programs (e.g., graph algorithms). This was previously demonstrated and tied to its architecture choices and ease-of-programming. In contrast, current commercial GPUs excel at regular parallel programs that require high processing capability. In this work, we set the power envelope as a constraint and evaluate an envisioned 1024-core XMT processor against an NVIDIA GTX280 GPU considering various scenarios for estimating the power of the XMT chip. Even under worst-case assumptions and scenarios, simulations show that the XMT processor sustains its advantage over the GPU on irregular parallel programs, while not falling significantly behind on regular programs. The total energy spent per benchmark fits a similar pattern. Given that the two architectures target different types of parallelism, a future system can potentially utilize an XMT chip and a GPU chip in complementary roles.
  • Keywords
    graphics processing units; multiprocessing systems; parallel programming; performance evaluation; power aware computing; NVIDIA GTX280 GPU; XMT chip; XMT general-purpose processor; general-purpose computing; graphics processing unit; many-core processor design point; parallel program; power envelope; power-performance comparison; single-task driven many-core; Benchmark testing; Clocks; Computer architecture; Graphics processing unit; Random access memory; Temperature measurement; GPU; PRAM; XMT; many-core; parallelism; power and performance comparison;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Systems (ICPADS), 2011 IEEE 17th International Conference on
  • Conference_Location
    Tainan
  • ISSN
    1521-9097
  • Print_ISBN
    978-1-4577-1875-5
  • Type

    conf

  • DOI
    10.1109/ICPADS.2011.101
  • Filename
    6121297