Efficient large-scale sparse LU factorization for fast radio frequency circuit simulation

doi:10.1177/10943420251400893

CSpace

	Efficient large-scale sparse LU factorization for fast radio frequency circuit simulation
	Feng, Guofeng 1,2; Wang, Hongyu 1,3; Guo, Zhuoqiang 1,2; Li, Mingzhen 1,2; Zhao, Tong 1,2; Jin, Zhou 4; Jia, Weile 1,2; Tan, Guangming 1,2; Sun, Ninghui 1,2
	2025-12-07
发表期刊	INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS
ISSN	1094-3420
页码	18
摘要	Sparse LU factorization is a fundamental operation in circuit simulation, and its efficiency directly impacts the overall simulation performance, particularly for large-scale circuits. As the demand for high-performance simulation of radio frequency (RF) circuits increases, driven by the proliferation of advanced wireless communication technologies such as 5G and WiFi, optimizing RF circuit simulation has become crucial. RF simulation matrices, often sparse, exhibit a unique structure characterized by dense blocks. This distinct structural pattern has been underexplored in prior works, resulting in suboptimal exploitation of available computational resources. In this paper, we address this gap by proposing a novel blocked format for the L and U factors in sparse LU factorization, explicitly tailored to the block structure inherent in RF matrices. This approach facilitates a more efficient representation of the data objects in LU factorization by preserving and exploiting the spatial locality of RF matrices. We then redesign the sparse LU factorization algorithm, aligning it with our proposed blocked storage format. Our algorithm leverages the inherent data locality present in RF matrices, which not only reduces memory transactions but also minimizes the need for costly indirect memory access that typically degrades performance. The proposed data format transformation is streamlined to remove redundant data movement, mitigating the memory-bound operations. Furthermore, we convert vector-based operations into matrix operations, which significantly enhances data reuse and enables more efficient parallelization at the data level. By aligning computational patterns with the underlying memory hierarchy, our method improves computational efficiency. Experimental results demonstrate that our approach substantially outperforms existing state-of-the-art implementations, achieving notable performance improvements, and thereby providing advanced support for high-performance large-scale RF circuit simulation.
关键词	sparse LU factorization RF circuit simulation performance optimization
DOI	10.1177/10943420251400893
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Interdisciplinary Applications ; Computer Science, Theory & Methods
WOS记录号	WOS:001631478200001
出版者	SAGE PUBLICATIONS LTD
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/42976
专题	中国科学院计算技术研究所
通讯作者	Li, Mingzhen
作者单位	1.Chinese Acad Sci, Inst Comp Technol, State Key Lab Processors, 6 Kexueyuan Nanlu, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Adv Interdisciplinary Sci, Beijing, Peoples R China 4.Zhejiang Univ, Zhejiang, Peoples R China
推荐引用方式 GB/T 7714	Feng, Guofeng,Wang, Hongyu,Guo, Zhuoqiang,et al. Efficient large-scale sparse LU factorization for fast radio frequency circuit simulation[J]. INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS,2025:18.
APA	Feng, Guofeng.,Wang, Hongyu.,Guo, Zhuoqiang.,Li, Mingzhen.,Zhao, Tong.,...&Sun, Ninghui.(2025).Efficient large-scale sparse LU factorization for fast radio frequency circuit simulation.INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS,18.
MLA	Feng, Guofeng,et al."Efficient large-scale sparse LU factorization for fast radio frequency circuit simulation".INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS (2025):18.