Efficient large-scale sparse LU factorization for fast radio frequency circuit simulation
文献类型：期刊论文
| 作者 | Feng, Guofeng2,3; Wang, Hongyu2,4; Guo, Zhuoqiang2,3; Li, Mingzhen2,3; Zhao, Tong2,3; Jin, Zhou1; Jia, Weile2,3; Tan, Guangming2,3; Sun, Ninghui2,3 |
| 刊名 | INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS
 |
| 出版日期 | 2025-12-07 |
| 页码 | 18 |
| 关键词 | sparse LU factorization RF circuit simulation performance optimization |
| ISSN号 | 1094-3420 |
| DOI | 10.1177/10943420251400893 |
| 英文摘要 | 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. |
| 资助项目 | China National Postdoctoral Program for Innovative Talents[BX20240383] ; National Science Foundation of China[62372435] ; National Science Foundation of China[92270206] ; National Science Foundation of China[62204265] ; National Science Foundation of China[92473107] ; Beijing Natural Science Foundation[4254087] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001631478200001 |
| 出版者 | SAGE PUBLICATIONS LTD |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/42975]  |
| 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.Zhejiang Univ, Zhejiang, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Processors, 6 Kexueyuan Nanlu, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Sch Adv Interdisciplinary Sci, Beijing, 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. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。