Performance Evaluation of Mixed-Precision Runge-Kutta Methods

Ben Burnett; Sigal Gottlieb; Zachary J. Grant; Alfa Heryudono

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arXiv · 2107.03357

Performance Evaluation of Mixed-Precision Runge-Kutta Methods

Ben Burnett·Sigal Gottlieb·Zachary J. Grant·Alfa Heryudono

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Abstract

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 or 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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Ben Burnett, Sigal Gottlieb, Zachary J. Grant, Alfa Heryudono. 2021-07-07. Performance Evaluation of Mixed-Precision Runge-Kutta Methods. https://arxiv.org/abs/2107.03357

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