On the preconditioner of conjugate gradient method — A power grid simulation perspective

Chung-Han Chou, Nien-Yu Tsai, Hao Yu, Che-Rung Lee, Yiyu Shi, Shih-Chieh Chang
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引用次数: 30

Abstract

Preconditioned Conjugate Gradient (PCG) method has been demonstrated to be effective in solving large-scale linear systems for sparse and symmetric positive definite matrices. One critical problem in PCG is to design a good preconditioner, which can significantly reduce the runtime while keeping memory usage efficient. Universal preconditioners are simple and easy to construct, but their effectiveness is highly problem-dependent. On the other hand, domain-specific preconditioners that explore the underlying physical meaning of the matrices usually work better, but are difficult to design. In this paper, we study the problem in the context of power grid simulation, and develop a novel preconditioner based on the power grid structure through simple circuit simulations. Experimental results show 43% reduction in the number of iterations and 23% speedup over existing universal preconditioners.
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论共轭梯度法的前置条件——一个电网仿真的视角
预条件共轭梯度法(PCG)已被证明是求解大规模线性系统的有效方法,该系统具有稀疏对称正定矩阵。在PCG中,一个关键问题是设计一个好的预调节器,它可以显著减少运行时间,同时保持内存使用效率。通用预调节器结构简单,易于构造,但其使用效果与实际问题高度相关。另一方面,探索矩阵的底层物理含义的领域特定前置条件通常工作得更好,但很难设计。本文在电网仿真的背景下对该问题进行了研究,并通过简单的电路仿真,开发了一种基于电网结构的新型预调节器。实验结果表明,与现有通用预调节器相比,迭代次数减少43%,速度提高23%。
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