A variant of the biconjugate gradient method suitable for massively parallel computing

被引:0
作者
Bucker, HM [1 ]
Sauren, M [1 ]
机构
[1] Forschungszentrum Julich, Zent Inst Angew Math, D-52425 Julich, Germany
来源
SOLVING IRREGULARLY STRUCTURED PROBLEMS IN PARALLEL | 1997年 / 1253卷
关键词
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Starting from a specific implementation of the Lanczos biorthogonalization algorithm, an iterative process for the solution of systems of Linear equations with general non-Hermitian coefficient matrix is derived. Due to the orthogonalization of the underlying Lanczos process the resulting iterative scheme involves inner products leading to global communication and synchronization on parallel processors. For massively parallel computers, these effects cause considerable delays often preventing the scalability of the implementation. In the process proposed, all inner product-like operations of an iteration step are independent such that the implementation consists of only a single global synchronization point per iteration. In exact arithmetic, the process is shown to be mathematically equivalent to the biconjugate gradient method. The efficiency of this new variant is demonstrated by numerical experiments on a PARAGON system using up to 121 processors.
引用
收藏
页码:72 / 79
页数:8
相关论文
共 50 条
  • [31] AN ANALYSIS OF THE COMPOSITE STEP BICONJUGATE GRADIENT-METHOD
    BANK, RE
    CHAN, TF
    NUMERISCHE MATHEMATIK, 1993, 66 (03) : 295 - 319
  • [32] Parallel power flow solutions using a biconjugate gradient algorithm and a Newton method: A GPU-based approach
    Facultad de Ingeniería Eléctrica, Universidad Michoacana de San Nicolás de Hidalgo, Mexico
    IEEE PES Gen. Meet., PES,
  • [33] Conservative and Implicit Method of Handling Unstructured Sliding Mesh in Massively Parallel Computing
    Xiao, Yi
    Guo, Kaixin
    Ming, Pingjian
    Ship Building of China, 2024, 65 (01) : 267 - 277
  • [34] GPU computing: Programming a massively parallel processor
    Buck, Ian
    CGO 2007: INTERNATIONAL SYMPOSIUM ON CODE GENERATION AND OPTIMIZATION, 2007, : 17 - 17
  • [35] Cluster of supercomputers - An alternative to massively parallel computing
    Mierendorff, H
    Schuller, A
    Trottenberg, U
    SUPERCOMPUTER, 1996, 12 (01): : 81 - 90
  • [36] ISSUES IN APPLYING MASSIVELY PARALLEL COMPUTING POWER
    DEMOS, G
    INTERNATIONAL JOURNAL OF SUPERCOMPUTER APPLICATIONS AND HIGH PERFORMANCE COMPUTING, 1990, 4 (04): : 90 - 105
  • [37] Massively parallel computing using commodity components
    Brightwell, R
    Fisk, LA
    Greenberg, DS
    Hudson, T
    Levenhagen, M
    Maccabe, AB
    Riesen, R
    PARALLEL COMPUTING, 2000, 26 (2-3) : 243 - 266
  • [38] WHAT IS MASSIVELY PARALLEL COMPUTING, AND WHY IS IT IMPORTANT
    HILLIS, WD
    DAEDALUS, 1992, 121 (01) : 1 - 15
  • [39] Massively parallel computing on an organic molecular layer
    Bandyopadhyay, Anirban
    Pati, Ranjit
    Sahu, Satyajit
    Peper, Ferdinand
    Fujita, Daisuke
    NATURE PHYSICS, 2010, 6 (05) : 369 - 375
  • [40] Program Execution Models for Massively Parallel Computing
    Dennis, Jack B.
    APPLICATIONS, TOOLS AND TECHNIQUES ON THE ROAD TO EXASCALE COMPUTING, 2012, 22 : 29 - 40