• DocumentCode
    625638
  • Title

    Cyclops Tensor Framework: Reducing Communication and Eliminating Load Imbalance in Massively Parallel Contractions

  • Author

    Solomonik, Edgar ; Matthews, Darin ; Hammond, Jeff R. ; Demmel, J.

  • Author_Institution
    Berkeley Dept. EECS, Univ. of California, Berkeley, Berkeley, CA, USA
  • fYear
    2013
  • fDate
    20-24 May 2013
  • Firstpage
    813
  • Lastpage
    824
  • Abstract
    Cyclops (cyclic-operations) Tensor Framework (CTF) 1 is a distributed library for tensor contractions. CTF aims to scale high-dimensional tensor contractions such as those required in the Coupled Cluster (CC) electronic structure method to massively-parallel supercomputers. The framework preserves tensor structure by subdividing tensors cyclically, producing a regular parallel decomposition. An internal virtualization layer provides completely general mapping support while maintaining ideal load balance. The mapping framework decides on the best mapping for each tensor contraction at run-time via explicit calculations of memory usage and communication volume. CTF employs a general redistribution kernel, which transposes tensors of any dimension between arbitrary distributed layouts, yet touches each piece of data only once. Sequential symmetric contractions are reduced to matrix multiplication calls via tensor index transpositions and partial unpacking. The user-level interface elegantly expresses arbitrary-dimensional generalized tensor contractions in the form of a domain specific language. We demonstrate performance of CC with single and double excitations on 8192 nodes of Blue Gene/Q and show that CTF outperforms NWChem on Cray XE6 supercomputers for benchmarked systems.
  • Keywords
    matrix multiplication; parallel processing; resource allocation; tensors; user interfaces; virtualisation; Blue Gene/Q; CC electronic structure method; CC performance; CTF; arbitrary distributed layouts; arbitrary-dimensional generalized tensor contractions; communication imbalance reduction; communication volume; coupled cluster electronic structure method; cyclic tensor subdivision; cyclic-operation tensor framework; cyclops tensor framework; distributed library; domain specific language; double excitations; general mapping support; general redistribution kernel; high-dimensional tensor contractions; ideal load balance; internal virtualization layer; load imbalance elimination; massively parallel contractions; massively-parallel supercomputers; matrix multiplication calls; memory usage; partial unpacking; regular parallel decomposition; sequential symmetric contractions; single excitations; tensor index transpositions; tensor structure preservation; user-level interface; Chemistry; Clustering algorithms; Equations; Indexes; Manganese; Program processors; Tensile stress; Coupled Cluster; Cyclops; communication-avoiding algorithms; tensor contractions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing (IPDPS), 2013 IEEE 27th International Symposium on
  • Conference_Location
    Boston, MA
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4673-6066-1
  • Type

    conf

  • DOI
    10.1109/IPDPS.2013.112
  • Filename
    6569864