Carmen Arévalo, Erik Jonsson-Glans, Josefine Olander, M. S. Soto, Gustaf Söderlind
{"title":"A Software Platform for Adaptive High Order Multistep Methods","authors":"Carmen Arévalo, Erik Jonsson-Glans, Josefine Olander, M. S. Soto, Gustaf Söderlind","doi":"10.1145/3372159","DOIUrl":null,"url":null,"abstract":"We present a software package, Modes, offering h-adaptive and p-adaptive linear multistep methods for first order initial value problems in ordinary differential equations. The implementation is based on a new parametric, grid-independent representation of multistep methods [Arévalo and Söderlind 2017]. Parameters are supplied for over 60 methods. For nonstiff problems, all maximal order methods (p=k for explicit and p=k+1 for implicit methods) are supported. For stiff computation, implicit methods of order p=k are included. A collection of step-size controllers based on digital filters is provided, generating smooth step-size sequences offering improved computational stability. Controllers may be selected to match method and problem classes. A new system for automatic order control is also provided for designated families of multistep methods, offering simultaneous h- and p-adaptivity. Implemented as a Matlab toolbox, the software covers high order computations with linear multistep methods within a unified, generic framework. Computational experiments show that the new software is competitive and offers qualitative improvements. Modes is available for downloading and is primarily intended as a platform for developing a new generation of state-of-the-art multistep solvers, as well as for true ceteris paribus evaluation of algorithmic components. This also enables method comparisons within a single implementation environment.","PeriodicalId":7036,"journal":{"name":"ACM Transactions on Mathematical Software (TOMS)","volume":"81 1","pages":"1 - 17"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Mathematical Software (TOMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3372159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We present a software package, Modes, offering h-adaptive and p-adaptive linear multistep methods for first order initial value problems in ordinary differential equations. The implementation is based on a new parametric, grid-independent representation of multistep methods [Arévalo and Söderlind 2017]. Parameters are supplied for over 60 methods. For nonstiff problems, all maximal order methods (p=k for explicit and p=k+1 for implicit methods) are supported. For stiff computation, implicit methods of order p=k are included. A collection of step-size controllers based on digital filters is provided, generating smooth step-size sequences offering improved computational stability. Controllers may be selected to match method and problem classes. A new system for automatic order control is also provided for designated families of multistep methods, offering simultaneous h- and p-adaptivity. Implemented as a Matlab toolbox, the software covers high order computations with linear multistep methods within a unified, generic framework. Computational experiments show that the new software is competitive and offers qualitative improvements. Modes is available for downloading and is primarily intended as a platform for developing a new generation of state-of-the-art multistep solvers, as well as for true ceteris paribus evaluation of algorithmic components. This also enables method comparisons within a single implementation environment.
我们提出了一个软件包,Modes,提供了常微分方程一阶初值问题的h-自适应和p-自适应线性多步方法。该实现基于多步骤方法的一种新的参数化、网格无关的表示[arsamuvalo and Söderlind 2017]。为60多个方法提供了参数。对于非刚性问题,支持所有最大阶方法(显式方法为p=k,隐式方法为p=k+1)。对于刚性计算,包括p=k阶的隐式方法。提供了一组基于数字滤波器的步长控制器,生成平滑的步长序列,提供了更好的计算稳定性。可以选择控制器来匹配方法和问题类别。自动订单控制的新系统也提供了指定的多步骤方法家族,同时提供h-和p-适应性。作为Matlab工具箱实现,该软件在统一的通用框架内涵盖了线性多步骤方法的高阶计算。计算实验表明,新软件具有竞争力,并提供了定性改进。Modes可供下载,主要用作开发新一代最先进的多步骤求解器的平台,以及对算法组件进行真正的同等条件评估。这还支持在单个实现环境中进行方法比较。