{"title":"CKTSO:用于通用电路仿真的高性能并行稀疏线性求解器","authors":"Xiaoming Chen","doi":"10.1109/TCAD.2024.3506215","DOIUrl":null,"url":null,"abstract":"This article introduces CKTSO (abbreviation of “circuit solver”), a novel sparse linear solver specially designed for the simulation program with integrated circuit emphasis (SPICE). CKTSO is a parallel solver and can be run on a multicore, shared-memory computer. The algorithms of CKTSO are designed by considering the features of matrices involved in SPICE simulations. CKTSO is superior to existing similar solvers mainly in the following three aspects. First, the matrix ordering step of CKTSO combines different types of ordering algorithms such that it can generally obtain the fewest fill-ins for a wide range of circuit matrices. Second, CKTSO provides a parallel fast LU factorization algorithm with pivot check, which behaves good performance, scalability, and numerical stability. Third, CKTSO provides a structure-adaptive hybrid parallel triangular solving algorithm, which can adapt to various circuit matrices. Experiments, including both benchmark tests and SPICE simulations, demonstrate the superior performance of CKTSO. The libraries of CKTSO are available at <uri>https://github.com/chenxm1986/cktso</uri>.","PeriodicalId":13251,"journal":{"name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","volume":"44 5","pages":"1887-1900"},"PeriodicalIF":2.7000,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CKTSO: High-Performance Parallel Sparse Linear Solver for General Circuit Simulations\",\"authors\":\"Xiaoming Chen\",\"doi\":\"10.1109/TCAD.2024.3506215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article introduces CKTSO (abbreviation of “circuit solver”), a novel sparse linear solver specially designed for the simulation program with integrated circuit emphasis (SPICE). CKTSO is a parallel solver and can be run on a multicore, shared-memory computer. The algorithms of CKTSO are designed by considering the features of matrices involved in SPICE simulations. CKTSO is superior to existing similar solvers mainly in the following three aspects. First, the matrix ordering step of CKTSO combines different types of ordering algorithms such that it can generally obtain the fewest fill-ins for a wide range of circuit matrices. Second, CKTSO provides a parallel fast LU factorization algorithm with pivot check, which behaves good performance, scalability, and numerical stability. Third, CKTSO provides a structure-adaptive hybrid parallel triangular solving algorithm, which can adapt to various circuit matrices. Experiments, including both benchmark tests and SPICE simulations, demonstrate the superior performance of CKTSO. The libraries of CKTSO are available at <uri>https://github.com/chenxm1986/cktso</uri>.\",\"PeriodicalId\":13251,\"journal\":{\"name\":\"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems\",\"volume\":\"44 5\",\"pages\":\"1887-1900\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10767386/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10767386/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
CKTSO: High-Performance Parallel Sparse Linear Solver for General Circuit Simulations
This article introduces CKTSO (abbreviation of “circuit solver”), a novel sparse linear solver specially designed for the simulation program with integrated circuit emphasis (SPICE). CKTSO is a parallel solver and can be run on a multicore, shared-memory computer. The algorithms of CKTSO are designed by considering the features of matrices involved in SPICE simulations. CKTSO is superior to existing similar solvers mainly in the following three aspects. First, the matrix ordering step of CKTSO combines different types of ordering algorithms such that it can generally obtain the fewest fill-ins for a wide range of circuit matrices. Second, CKTSO provides a parallel fast LU factorization algorithm with pivot check, which behaves good performance, scalability, and numerical stability. Third, CKTSO provides a structure-adaptive hybrid parallel triangular solving algorithm, which can adapt to various circuit matrices. Experiments, including both benchmark tests and SPICE simulations, demonstrate the superior performance of CKTSO. The libraries of CKTSO are available at https://github.com/chenxm1986/cktso.
期刊介绍:
The purpose of this Transactions is to publish papers of interest to individuals in the area of computer-aided design of integrated circuits and systems composed of analog, digital, mixed-signal, optical, or microwave components. The aids include methods, models, algorithms, and man-machine interfaces for system-level, physical and logical design including: planning, synthesis, partitioning, modeling, simulation, layout, verification, testing, hardware-software co-design and documentation of integrated circuit and system designs of all complexities. Design tools and techniques for evaluating and designing integrated circuits and systems for metrics such as performance, power, reliability, testability, and security are a focus.