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arXiv 2407.15973math.NAcs.MScs.NA
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混合精度块雅可比预处理器:算法、性能评估与特征分析

Mixed Precision Block-Jacobi Preconditioner: Algorithms, Performance Evaluation and Feature Analysis

Ningxi Tian, Silu Huang, Xiaowen Xu

AI总结:

本文针对Block-Jacobi预处理器提出固定和自适应两种混合精度策略,结合预处理共轭梯度算法进行测试,在保持精度的同时实现1.3至1.8倍加速,并分析了收敛延迟现象及其矩阵特征。

摘要:

本文针对Block-Jacobi预处理器(BJAC)提出了两种混合精度算法:固定低精度策略和自适应精度策略。我们利用扩散方程和辐射流体力学方程等问题,评估了所提出的混合精度BJAC预处理器与预处理共轭梯度算法结合后的性能提升。数值结果表明,与统一高精度的PCG算法相比,混合精度预处理器在保持精度的同时可实现1.3到1.8倍的加速。此外,我们观察到在某些测试用例中混合精度预处理器出现了收敛延迟现象,并进一步分析了与收敛延迟行为相关的矩阵特征。

英文摘要:

In this paper, we propose two mixed precision algorithms for Block-Jacobi preconditioner(BJAC): a fixed low precision strategy and an adaptive precision strategy. We evaluate the performance improvement of the proposed mixed precision BJAC preconditioners combined with the preconditioned conjugate gradient algorithm using problems including diffusion equations and radiation hydrodynamics equations. Numerical results show that, compared to the uniform high precision PCG algorithm, the mixed precision preconditioners can achieve speedups from 1.3 to 1.8 without sacrificing accuracy. Furthermore, we observe the phenomenon of convergence delay in some test cases for the mixed precision preconditioners, and further analyse the matrix features associate with the convergence delay behavior.

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