稀疏矩阵运算器课程设计参考文献

稀疏矩阵运算器课程设计参考文献参考文献:
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[3] Y.J. Gao,T. Wang, J.J.Liu. Introduction to Sparse Matrix Algorithm Research [J]. Journal of Computer Research and Development, 2019, 56(8): 1587–1603.
[4] S. Słowikowski, A. Strzelecki, L. Wainstein, M. Paszyński, M. Stolarska. High-performance Solvers of Sparse Linear Systems for Engineering Applications [J]. Computer Methods in Applied Mechanics and Engineering, 2017, 327: 1-37.
[5] J.Wang, J. Xiang, J. Zhang. An Overview of Sparse Matrix Techniques and Applications [J]. Journal of Engineering Mathematics, 2019, 115(1):
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[6] T. Davis, S. Rajamanickam, and W. Wu. A Runtime Analysis of High-Performance Sparse Linear Algebra Libraries on Multicore CPUs and GPUs [J]. SIAM Journal on Scientific Computing, 2017, 39(5): C534-C563.
[7] X. Zhang, Y. Zhong and X. Liu. Development of Sparse Matrix Method in Engineering and Its Applications [J]. Journal of Mechanical Engineering, 2017, 53(24): 17-29.
[8] H. Chen, Wang Pei, X. Zhang, B. Gong. Development of Sparse Matrix and Its Applications in Structural Engineering [J]. Engineering Mechanics, 2020, 37(S2): 42-50.
[9] N. Cai, T. Wang, Y.J. Gao, X. Wang. Sparse Matrix Solver Techniques and Applications [J]. Applied Mathematics and Mechanics, 2020, 41(1): 1-25.
[10] X. Zhang, L. Wang, S. Dai, H. Guo. Sparse Matrix Methods for Structural Analysis and Optimization [J]. Archives of Computational Methods in Engineering, 2018, 25(4): 903-939.
本文列举了一些与稀疏矩阵算法领域相关的学术论文。

这些文献介绍了稀疏矩阵算法的发展历程、实现技术、性能优化以及在各个领域中的应用。

同时，它们也为研究者提供了宝贵的经验，以指导开发高效的稀疏矩阵运算器并更好地服务于实际应用。