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Performance Evaluation of Mixed-Precision Runge-Kutta Methods
Conference proceeding

Performance Evaluation of Mixed-Precision Runge-Kutta Methods

Ben Burnett, Sigal Gottlieb, Zachary J. Grant and Alfa Heryudono
IEEE Conference on High Performance Extreme Computing (Online), pp.1-6
09/20/2021

Abstract

Additives Codes Conferences Mixed-precision multiprecision numerical methods Ordinary differential equations Performance evaluation Runge-Kutta Runtime Energy Consumption
Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were proposed and analyzed in [8]. These specially designed methods use reduced precision for the implicit computations and full precision for the explicit computations. We develop a FORTRAN code to solve a nonlinear system of ordinary differential equations using the mixed precision additive Runge-Kutta (MP-ARK) methods on IBM POWER9 and Intel x86_64 chips. The convergence, accuracy, runtime, and energy consumption of these methods is explored. We show that these MP-ARK methods efficiently produce accurate solutions with significant reductions in runtime (and by extension energy consumption).

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