Fast Finite Element Analysis with Reduced-Precision Arithmetic

Abstract

In most CAE simulations based on the finite element method, double-precision real numbers have been used. On the other hand, due to overwhelming demand for deep learning, low-precision arithmetic is now being introduced into general-purpose processors. By using low-precision real arithmetic for finite element analyses, we can effectively use the arithmetic unit originally equipped for deep learning and obtain advantages in terms of calculation speed. In this study, we propose a fast finite element analysis assisted by deep learning, where low-precision arithmetic is aggressively used to accelerate calculation speed. In the proposed method, deep learning indicates where to use lower precision computation for calculation speed. Here, for the first try, the effect of low precision numbers on numerical quadrature of finite elements is quantitatively investigated through sample analyses.