L.P. da Silva , C.H. Marchi , M. Meneguette , R. Suero
{"title":"使用鲁棒代数多级法快速收敛 SPH 数值解法","authors":"L.P. da Silva , C.H. Marchi , M. Meneguette , R. Suero","doi":"10.1016/j.jocs.2024.102369","DOIUrl":null,"url":null,"abstract":"<div><p>In our study we solve 2D equations that model the mathematical phenomenon of steady state heat diffusion. The discretization of the equations is performed with the smoothed particle hydrodynamics (SPH) method and the resolution of the associated system of linear equations is determined with a modified solver that we call the Gauss–Seidel–Silva (G–S–S). The single level parallel G–S–S solver is compared to the algebraic multilevel (AML) with serial G–S–S smoother which has the ability to smooth the error of the numerical solutions and accelerate convergence due to its iterative formulation. The AML with serial G–S–S smoother is responsible for determining speed-ups of 4084 times for uniform and 5136 times for non-uniform particle discretization. We estimate a speed-up of 41082 times for the AML with parallel G–S–S smoother.</p></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"81 ","pages":"Article 102369"},"PeriodicalIF":3.1000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast convergence of SPH numerical solutions using robust algebraic multilevel\",\"authors\":\"L.P. da Silva , C.H. Marchi , M. Meneguette , R. Suero\",\"doi\":\"10.1016/j.jocs.2024.102369\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In our study we solve 2D equations that model the mathematical phenomenon of steady state heat diffusion. The discretization of the equations is performed with the smoothed particle hydrodynamics (SPH) method and the resolution of the associated system of linear equations is determined with a modified solver that we call the Gauss–Seidel–Silva (G–S–S). The single level parallel G–S–S solver is compared to the algebraic multilevel (AML) with serial G–S–S smoother which has the ability to smooth the error of the numerical solutions and accelerate convergence due to its iterative formulation. The AML with serial G–S–S smoother is responsible for determining speed-ups of 4084 times for uniform and 5136 times for non-uniform particle discretization. We estimate a speed-up of 41082 times for the AML with parallel G–S–S smoother.</p></div>\",\"PeriodicalId\":48907,\"journal\":{\"name\":\"Journal of Computational Science\",\"volume\":\"81 \",\"pages\":\"Article 102369\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Science\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1877750324001625\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Science","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1877750324001625","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Fast convergence of SPH numerical solutions using robust algebraic multilevel
In our study we solve 2D equations that model the mathematical phenomenon of steady state heat diffusion. The discretization of the equations is performed with the smoothed particle hydrodynamics (SPH) method and the resolution of the associated system of linear equations is determined with a modified solver that we call the Gauss–Seidel–Silva (G–S–S). The single level parallel G–S–S solver is compared to the algebraic multilevel (AML) with serial G–S–S smoother which has the ability to smooth the error of the numerical solutions and accelerate convergence due to its iterative formulation. The AML with serial G–S–S smoother is responsible for determining speed-ups of 4084 times for uniform and 5136 times for non-uniform particle discretization. We estimate a speed-up of 41082 times for the AML with parallel G–S–S smoother.
期刊介绍:
Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory.
The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation.
This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods.
Computational science typically unifies three distinct elements:
• Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous);
• Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems;
• Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).