摘要
线性方程组解法器库X-Solver旨在实现并优化Krylov子空间求解方法与预条件算法,用于在配备GPU加速卡的分布式内存机群上高效求解大规模稀疏线性方程组.结合实际应用需求与硬件架构趋势,我们在以下三个方面实现了突破:(1)提供用户友好、易于集成的分布式计算支持;(2)深度适配异构架构特征,充分挖掘硬件计算潜力;(3)保持跨多种硬件平台的高性能可移植性.数值实验表明,在目标硬件上,X-Solver相较于其它先进解法器库在多个典型应用中展现出优势.
The X-Solver library aims to implement and optimize Krylov subspace solution methods and preconditioners to solve large and sparse linear systems of equations on distributed memory clusters equipped with many-core GPUs as accelerators.Motivated by the requirements from real-world applications and the trend of hardware integrations,we manage three achievements,i.e.,more effective support for distributed calculations,better exploitation of characteristics of modern many-core architectures,and portability across different heterogeneous platforms.Numerical experiments demonstrate advantages over other state-of-the-art libraries in a broad range of applications on the targeting hardware.
作者
汪云婷
杨少峰
何鑫
谭光明
Wang yunting;Yang shaofeng;He xin;Tan guangming(Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China)
出处
《数值计算与计算机应用》
2025年第4期296-320,共25页
Journal on Numerical Methods and Computer Applications
基金
国家自然科学基金(62172389)资助.
