Improving solve time of aggregation-based adaptive AMG

被引:9
|
作者
D'Ambra, Pasqua [1 ]
Vassilevski, Panayot S. [2 ,3 ]
机构
[1] CNR, Inst Appl Comp Mauro Picone, Via P Castellino 111, I-80131 Naples, Italy
[2] Lawrence Livermore Natl Lab, Ctr Appl Sci Comp, Livermore, CA 94550 USA
[3] Portland State Univ, Fariborz Maseeh Dept Math & Stat, Portland, OR 97207 USA
基金
欧盟地平线“2020”;
关键词
adaptive AMG; compatible relaxation; solve time; unsmoothed aggregation; weighted matching; RELAXATION; ALGORITHMS; MATCHINGS;
D O I
10.1002/nla.2269
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper proposes improving the solve time of a bootstrap algebraic multigrid (AMG) designed previously by the authors. This is achieved by incorporating the information, a set of algebraically smooth vectors, generated by the bootstrap algorithm, in a single hierarchy by using sufficiently large aggregates, and these aggregates are compositions of aggregates already built throughout the bootstrap algorithm. The modified AMG method has good convergence properties and shows significant reduction in both memory and solve time. These savings with respect to the original bootstrap AMG are illustrated on some difficult (for standard AMG) linear systems arising from discretization of scalar and vector function elliptic partial differential equations in both 2D and 3D.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] A Multi-GPU Aggregation-Based AMG Preconditioner for Iterative Linear Solvers
    Bernaschi, Massimo
    Celestini, Alessandro
    Vella, Flavio
    D'Ambra, Pasqua
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2023, 34 (08) : 2365 - 2376
  • [2] Adaptive aggregation-based domain decomposition multigrid for twisted mass fermions
    Alexandrou, Constantia
    Bacchio, Simone
    Finkenrath, Jacob
    Frommer, Andreas
    Kahl, Karsten
    Rottmann, Matthias
    PHYSICAL REVIEW D, 2016, 94 (11)
  • [3] Analysis of aggregation-based multigrid
    Muresan, Adrian C.
    Notay, Yvan
    SIAM JOURNAL ON SCIENTIFIC COMPUTING, 2008, 30 (02): : 1082 - 1103
  • [4] Information gain Aggregation-based Approach for Time Series Shapelets Discovery
    Kramakum, Chutimol
    Rakthanmanon, Thanawin
    Waiyamai, Kitsana
    PROCEEDINGS OF 2018 10TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (KSE), 2018, : 97 - 101
  • [5] Aggregation-based fault diagnosis algorithms
    Sliwinski, Przemyslaw
    Wachel, Pawel
    Hasiewicz, Zygmunt
    Lagosz, Szymon
    IFAC PAPERSONLINE, 2018, 51 (24): : 488 - 493
  • [6] Aggregation-based QoS routing in the internet
    Hou R.
    Leung K.-C.
    Lui K.-S.
    Leung K.-C.
    Baker F.
    Journal of Communications, 2010, 5 (03): : 239 - 246
  • [7] AN AGGREGATION-BASED ALGEBRAIC MULTIGRID METHOD
    Notay, Yvan
    ELECTRONIC TRANSACTIONS ON NUMERICAL ANALYSIS, 2010, 37 : 123 - 146
  • [8] Algebraic analysis of aggregation-based multigrid
    Napov, Artem
    Notay, Yvan
    NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS, 2011, 18 (03) : 539 - 564
  • [9] Aggregation-based algebraic multilevel preconditioning
    Notay, Y
    SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 2006, 27 (04) : 998 - 1018
  • [10] Aggregation-based extensions of fuzzy measures
    Kolesarova, Anna
    Stupnanova, Andrea
    Beganova, Juliana
    FUZZY SETS AND SYSTEMS, 2012, 194 : 1 - 14