数据结构算法在电力系统稀疏矩阵计算中的应用

2021 International Conference in Advances in Power, Signal, and Information Technology (APSIT) Pub Date : 2021-10-08 DOI:10.1109/APSIT52773.2021.9641231

Subhranshu Sekhar Puhan, Sobhit Panda, S. Lenka, Renu Sharma

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引用次数: 0

摘要

稀疏矩阵在大多数工程/科学应用中使用/出现。由于稀疏代码要显式地处理特定的数据结构，因此在编译器的优化方面存在一个问题。这种数据结构与程序的有用性关系太大，以致限制了程序的增强。本文讨论了各种数据结构选择方法以及延迟数据结构选择到编译阶段的概述。使用这种延迟数据结构方法可以生成高效的稀疏矩阵计算代码。将详细的方法应用于电力系统分析中并行高斯技术中的逻辑单元分解。

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Application of Data Structure Algorithm For Sparse Matrix Computation in Power System

Sparse matrices are used/occur in most of the engineering/scientific applications. There has been a problem in optimization of compiler of sparse codes as they explicitly deal with particular data structure. This data structure dealing with the usefulness of a program so much that enhancement of the program is restricted. In this paper various methods of Data structure selection methodologies along with overview of delays data structure selection till compilation phase is discussed. Efficient code is generated for sparse matrix computations using this delayed Data structure method. The detailed methodology is applied in LU decomposition in Parallel Gauss techniques in Power System Analysis.

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2021 International Conference in Advances in Power, Signal, and Information Technology (APSIT)

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