• DocumentCode
    3664148
  • Title

    Early Multi-node Performance Evaluation of a Knights Corner (KNC) Based NASA Supercomputer

  • Author

    Subhash Saini;Haoqiang Jin;Dennis Jespersen;Samson Cheung;Jahed Djomehri;Johnny Chang;Robert Hood

  • Author_Institution
    NASA Adv. Supercomput. (NAS) Div., NASA Ames Res. Center, Moffett Field, CA, USA
  • fYear
    2015
  • fDate
    5/1/2015 12:00:00 AM
  • Firstpage
    57
  • Lastpage
    67
  • Abstract
    We have conducted performance evaluation of a dual-rail Fourteen Data Rate (FDR) InfiniBand (IB) connected cluster, where each node has two Intel Xeon E5-2670 (Sandy Bridge) processors and two Intel Xeon Phi coprocessors. The Xeon Phi, based on the Many Integrated Core (MIC) architecture, is of the Knights Corner (KNC) generation. We used several types of benchmarks for the study. We ran the MPI and multi-zone versions of the NAS Parallel Benchmarks (NPB) -- both original and optimized for the Xeon Phi. Among the full-scale benchmarks, we ran two versions of WRF, including one optimized for the MIC, and used a 12 Km Continental U.S (CONUS) data set. We also used original and optimized versions of OVERFLOW and ran with four different datasets to understand scaling in symmetric mode and related load-balancing issues. We present performance for the four different modes of using the host + MIC combination: native host, native MIC, offload, and symmetric. We also discuss the various optimization techniques used in optimizing two of the NPBs for offload mode as well as WRF and OVERFLOW. WRF 3.4 optimized for MIC runs 47% faster than the original NCAR WRF 3.4. The optimized version of OVERFLOW runs 18% faster on the host and the load-balancing strategy used improves the performance on MIC by 5% to 36% depending on the data size. In addition, we discuss the issues related to offload mode and load balancing in symmetric mode.
  • Keywords
    "Microwave integrated circuits","Coprocessors","Benchmark testing","Bridges","Bandwidth","Instruction sets"
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing Symposium Workshop (IPDPSW), 2015 IEEE International
  • Type

    conf

  • DOI
    10.1109/IPDPSW.2015.140
  • Filename
    7284290