JXPAMG: a parallel algebraic multigrid solver for extreme-scale numerical simulations

JXPAMG is a parallel algebraic multigrid (AMG) solver for solving the extreme-scale, sparse linear systems on modern supercomputers. JXPAMG features the following characteristics: 1) It integrates some application-driven parallel AMG algorithms, including αSetup-AMG (adaptive Setup based AMG), AI-AM...

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Bibliographic Details
Published in:CCF transactions on high performance computing (Online) 2023-03, Vol.5 (1), p.72-83
Main Authors: Xu, Xiaowen, Yue, Xiaoqiang, Mao, Runzhang, Deng, Yuntong, Huang, Silu, Zou, Haifeng, Liu, Xiao, Hu, Shaoliang, Feng, Chunsheng, Shu, Shi, Mo, Zeyao
Format: Article
Language:English
Subjects:
Adaptive algorithms
Algebra
Algorithms
Computer architecture
Computer Hardware
Computer Science
Computer Systems Organization and Communication Networks
Data structures
Efficiency
Iterative methods
Linear systems
Matrix algebra
Mechanics
New Algorithms and Software for E-Scale High Performance Computing
Partial differential equations
Regular Paper
Simulation
Software
Solvers
Sparse matrices
Sparsity
Supercomputers
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Summary:JXPAMG is a parallel algebraic multigrid (AMG) solver for solving the extreme-scale, sparse linear systems on modern supercomputers. JXPAMG features the following characteristics: 1) It integrates some application-driven parallel AMG algorithms, including αSetup-AMG (adaptive Setup based AMG), AI-AMG (algebraic interface based AMG) and AMG-PCTL (physical-variable based coarsening two-level AMG); 2) A hierarchical parallel sparse matrix data structure, labeled hierarchical parallel Compressed Sparse Row (hpCSR), that matches the computer architecture is designed, and the highly scalable components based on hpCSR are implemented; 3) A flexible software architecture is designed to separate algorithm development from implementation. These characteristics allow JXPAMG to use different AMG strategies for different application features and architecture features, and thereby JXPAMG becomes aware of changes in these features. This paper introduces the algorithms, implementation techniques and applications of JXPAMG. Numerical experiments for typical real applications are given to illustrate the strong and weak parallel scaling properties of JXPAMG.
ISSN:2524-4922
2524-4930
DOI:10.1007/s42514-022-00125-9