线性方程组的并行求解 - 共轭梯度法与数据并行 - 常规

线性方程组的并行求解 - 共轭梯度法与数据并行

线性方程组的并行求解是高性能计算领域的重要研究方向之一。共轭梯度法是一种常用的迭代方法，适用于求解大型稀疏线性方程组。数据并行技术可以有效地将计算任务分配到多个处理器上，从而加速求解过程。

本文主要介绍了共轭梯度法和数据并行技术在解决线性方程组问题中的应用，以及相关领域的经典书籍和文献。

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Bjorck, A., & Dahlquist, G. (1996). Numerical methods in scientific computing (Vol. 1). SIAM.
Demmel, J. (1997). Applied numerical linear algebra. Society for Industrial and Applied Mathematics.
Greenbaum, A. (1997). Iterative methods for solving linear systems. SIAM.
Strang, G. (1986). Introduction to applied mathematics. Wellesley-Cambridge Press.
Trefethen, L. N., & Bau III, D. (1997). Numerical linear algebra. Society for Industrial and Applied Mathematics.
Van der Vorst, H. A. (2003). Iterative Krylov methods for large linear systems. Cambridge University Press.
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Walker, H. F. (2001). Implementing parallel linear algebra algorithms. Springer.