Communications on Applied Mathematics and Computation ›› 2024, Vol. 6 ›› Issue (1): 705-738.doi: 10.1007/s42967-023-00315-4

• ORIGINAL PAPERS • 上一篇    下一篇

Stability Analysis and Performance Evaluation of Additive Mixed-Precision Runge-Kutta Methods

Ben Burnett1, Sigal Gottlieb1, Zachary J. Grant2   

  1. 1. Center for Scientific Computing and Data Science Research, UMass Dartmouth, North Dartmouth, Massachusetts, USA;
    2. CSME, Michigan State University, East Lansing, Michigan, USA
  • 收稿日期:2022-12-16 修回日期:2023-09-07 发布日期:2024-04-16
  • 通讯作者: Sigal Gottlieb,E-mail:sgottlieb@umassd.edu;Ben Burnett,E-mail:bburnett@umassd.edu;Zachary J. Grant,E-mail:zack.j.grant@gmail.com E-mail:sgottlieb@umassd.edu;bburnett@umassd.edu;zack.j.grant@gmail.com
  • 基金资助:
    Burnett and Gottlieb’s work was partially supported by ONR UMass Dartmouth Marine and UnderSea Technology (MUST) grant N00014-20-1-2849 under the project S31320000049160, by DOE grant DE-SC0023164 sub-award RC114586-UMD, and by AFOSR grants FA9550-18-1-0383 and FA9550-23-1-0037. Grant’s work was partially supported by Michigan State University, by AFOSR grants FA9550-19-1-0281 and FA9550-18-1-0383 and by DOE grant DE-SC0023164.

Stability Analysis and Performance Evaluation of Additive Mixed-Precision Runge-Kutta Methods

Ben Burnett1, Sigal Gottlieb1, Zachary J. Grant2   

  1. 1. Center for Scientific Computing and Data Science Research, UMass Dartmouth, North Dartmouth, Massachusetts, USA;
    2. CSME, Michigan State University, East Lansing, Michigan, USA
  • Received:2022-12-16 Revised:2023-09-07 Published:2024-04-16
  • Contact: Sigal Gottlieb,E-mail:sgottlieb@umassd.edu;Ben Burnett,E-mail:bburnett@umassd.edu;Zachary J. Grant,E-mail:zack.j.grant@gmail.com E-mail:sgottlieb@umassd.edu;bburnett@umassd.edu;zack.j.grant@gmail.com
  • Supported by:
    Burnett and Gottlieb’s work was partially supported by ONR UMass Dartmouth Marine and UnderSea Technology (MUST) grant N00014-20-1-2849 under the project S31320000049160, by DOE grant DE-SC0023164 sub-award RC114586-UMD, and by AFOSR grants FA9550-18-1-0383 and FA9550-23-1-0037. Grant’s work was partially supported by Michigan State University, by AFOSR grants FA9550-19-1-0281 and FA9550-18-1-0383 and by DOE grant DE-SC0023164.

摘要: Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were previously proposed and analyzed. These specially designed methods use reduced precision for the implicit computations and full precision for the explicit computations. In this work, we analyze the stability properties of these methods and their sensitivity to the low-precision rounding errors, and demonstrate their performance in terms of accuracy and efficiency. We develop codes in FORTRAN and Julia to solve nonlinear systems of ODEs and PDEs using the mixed-precision additive Runge-Kutta (MP-ARK) methods. The convergence, accuracy, and runtime of these methods are explored. We show that for a given level of accuracy, suitably chosen MP-ARK methods may provide significant reductions in runtime.

关键词: Mixed precision, Runge-Kutta methods, Additive methods, Accuracy

Abstract: Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were previously proposed and analyzed. These specially designed methods use reduced precision for the implicit computations and full precision for the explicit computations. In this work, we analyze the stability properties of these methods and their sensitivity to the low-precision rounding errors, and demonstrate their performance in terms of accuracy and efficiency. We develop codes in FORTRAN and Julia to solve nonlinear systems of ODEs and PDEs using the mixed-precision additive Runge-Kutta (MP-ARK) methods. The convergence, accuracy, and runtime of these methods are explored. We show that for a given level of accuracy, suitably chosen MP-ARK methods may provide significant reductions in runtime.

Key words: Mixed precision, Runge-Kutta methods, Additive methods, Accuracy