High energy & nuclear physics


Rmax = 33862 (i.e., 33,9 Pflops) – Rpeak = 54902 (computing efficiency : 61,7 %)



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Rmax = 33862 (i.e., 33,9 Pflops) – Rpeak = 54902 (computing efficiency : 61,7 %)

  • 3,120,000 cores – Memory: 1.375 PB – Disk: 12,4 PB –fat-tree based Interconnection Network

  • 16000 computer nodes

  • 1 node = 2 Intel (12 cores) Ivy Bridge Xeon + 3 (57 cores) Xeon Phi co-procs + 88GB memory shared by the Ivy Bridges procs + 8 GB memory shared by the Xeon Phi chips

  • Power:17,8 MW (1,9 Tflops/kW – 1,9 Gflops/W … only!)

  • « Tianhe-2 operation for 1 hour is equivalent to 1.3 billion people calculator operating one thousand years » (best-news.us – assertion not checked)



  • Top500.org

    • Top500.org

      • performance development
      • logarithmic progression! (x10 in 3years)
      • clusters, clusters (86%)!
      • 51% in industry
      • max power efficiency: 5,3 Gflops/W
      • #500: 153 TFlops! – Total : 309 Pflops
      • poster Top500
    • Graph500.org

      • BlueGene++
    • Green500.org and GreenGraph500

      • List
      • max: 5,3 Gflops/W
      • #1 green500 = #168 top500 (317-594 Tflops)
      • #1 top500 = #57 green500 (2GFlops/W)


    From LAN (cluster) computing to WAN computing

    • From LAN (cluster) computing to WAN computing

    • Set of machines distributed over a MAN/WAN that are used to execute parallel loosely coupled codes

    • Depending on the infrastructure (soft and hard), network computing is derived in Internet computing, P2P, Grid computing, etc.



    Definitions become fuzzy...

    • Definitions become fuzzy...

    • A meta computer = set of (widely) distributed (high performance) processing resources that can be associated for processing a parallel not so loosely coupled code

    • A meta computer = parallel

    • virtual machine over a

    • distributed system



    Use of (idle) computer interconnected by Internet for processing large throughput applications

    • Use of (idle) computer interconnected by Internet for processing large throughput applications

    • Ex: SETI@HOME

      • 5M+ users since launching
      • 20013/10: 1,4M users, 3,5M computers; 135k active users, 190k active computers
      • 625 Tflops (average 505 Tflops)!
      • 233 « countries »
      • 2M years of CPU time since 1999;
      • BOINC infrastructure (Décrypthon, RSA-155…)
      • much less active than it used to be (:2 since 2011)
    • Programmer view: a single master, n servants





    Internet computing on a pool of sites

    • Internet computing on a pool of sites

    • Meta computing with loosely coupled codes

    • Grid computing with poor communication facilities

    • Ex: Condor (invented in the 80’s)



    A site is both client and server: servent

    • A site is both client and server: servent

    • Dynamic servent discovery by « contamination »

    • 2 approaches:

      • centralized management: Napster, Kazaa, eDonkey…
      • distributed management: Gnutella, KAD, Freenet, Bittorrent…
    • Applications: file sharing, video delivery, collaborative computing



    Coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organisations” (I. Foster)

    • Coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organisations” (I. Foster)



    Information grid

    • Information grid

      • Large access to distributed data (the Web)
    • Data grid

      • Management and processing of very large distributed data sets – Data intensive computing
    • Computing grid

      • Meta computer




    Grids date back “only” 1996

    • Grids date back “only” 1996

    • Parallelism is older! (first classification in 1972)

    • Motivations:

      • need more computing power (weather forecast, atomic simulation, genomics…)
      • need more storage capacity (Petabytes and more)
      • in a word: improve performance! 3 ways ...
      • Work harder --> Use faster hardware
      • Work smarter --> Optimize algorithms
      • Get help --> Use more computers !



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