• DocumentCode
    1783333
  • Title

    A New Scalable Parallel Algorithm for Fock Matrix Construction

  • Author

    Xing Liu ; Patel, Anup ; Chow, Edmond

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • fYear
    2014
  • fDate
    19-23 May 2014
  • Firstpage
    902
  • Lastpage
    914
  • Abstract
    Hartree-Fock (HF) or self-consistent field (SCF) calculations are widely used in quantum chemistry, and are the starting point for accurate electronic correlation methods. Existing algorithms and software, however, may fail to scale for large numbers of cores of a distributed machine, particularly in the simulation of moderately-sized molecules. In existing codes, HF calculations are divided into tasks. Fine-grained tasks are better for load balance, but coarse-grained tasks require less communication. In this paper, we present a new parallelization of HF calculations that addresses this trade-off: we use fine grained tasks to balance the computation among large numbers of cores, but we also use a scheme to assign tasks to processes to reduce communication. We specifically focus on the distributed construction of the Fock matrix arising in the HF algorithm, and describe the data access patterns in detail. For our test molecules, our implementation shows better scalability than NWChem for constructing the Fock matrix.
  • Keywords
    HF calculations; chemistry computing; matrix algebra; parallel algorithms; Fock matrix construction; HF calculations; Hartree-Fock calculations; SCF calculations; coarse-grained task assignment; communication reduction; data access patterns; distributed machine; fine-grained tasks; load balancing; moderately-sized molecule simulation; parallelization; scalable parallel algorithm; self-consistent field calculations; Approximation algorithms; Approximation methods; Dynamic scheduling; Equations; Hafnium; Heuristic algorithms; Partitioning algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing Symposium, 2014 IEEE 28th International
  • Conference_Location
    Phoenix, AZ
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4799-3799-8
  • Type

    conf

  • DOI
    10.1109/IPDPS.2014.97
  • Filename
    6877321