• DocumentCode
    1783352
  • Title

    An Accelerated Recursive Doubling Algorithm for Block Tridiagonal Systems

  • Author

    Seal, Sudip K.

  • Author_Institution
    Oak Ridge Nat. Lab., Oak Ridge, TN, USA
  • fYear
    2014
  • fDate
    19-23 May 2014
  • Firstpage
    1019
  • Lastpage
    1028
  • Abstract
    Block tridiagonal systems of linear equations arise in a wide variety of scientific and engineering applications. Recursive doubling algorithm is a well-known prefix computation-based numerical algorithm that requires O(M3(N/P + log P)) work to compute the solution of a block tridiagonal system with N block rows and block size M on F processors. In real-world applications, solutions of tridiagonal systems are most often sought with multiple, often hundreds and thousands, of different right hand sides but with the same tridiagonal matrix. Here, we show that a recursive doubling algorithm is sub-optimal when computing solutions of block tridiagonal systems with multiple right hand sides and present a novel algorithm, called the accelerated recursive doubling algorithm, that delivers O(R) improvement when solving block tridiagonal systems with R distinct right hand sides. Since R is typically ~102 - 104, this improvement translates to very significant speedups in practice. Detailed complexity analyses of the new algorithm with empirical confirmation of runtime improvements are presented. To the best of our knowledge, this algorithm has not been reported before in the literature.
  • Keywords
    computational complexity; mathematics computing; matrix algebra; parallel algorithms; accelerated recursive doubling algorithm; block tridiagonal system; complexity analysis; engineering applications; linear equations; parallel solver; prefix computation-based numerical algorithm; runtime improvements; scientific applications; sub-optimal algorithm; tridiagonal matrix; Acceleration; Algorithm design and analysis; Bismuth; Complexity theory; Computer architecture; Program processors; Runtime; block tridiagonal matrix; cyclic reduction; parallel solver; prefix computation;
  • 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.2014.107
  • Filename
    6877331