Impact of low floating-point precision on high-fidelity simulations of turbulence

Modern computing clusters offer specialized hardware with reduced-precision arithmetic that can speed-up the time to solution significantly, mainly due to less data movement and increased arithmetic performance. However, for high-fidelity simulations of turbulence, separation, and transition the impact of lower floating-point precision on the computed solution and the uncertainty it introduces has not been explored in sufficient detail. This limits the optimal utilization of new and upcoming exascale machines. In this work, the effect of reduced precision for numerical solution of the Navier-Stokes equations is considered across different spatial and temporal discretization approaches. We compare four solvers, two compressible and two incompressible, across three test cases: K-type transition in a channel, turbulent channel flow up to Ret=2000 and flow over a cylinder at ReD=3900. Different terms of the Navier-Stokes equations are perturbed to lower floating-point precision, ranging from conventional 64 bit IEEE double precision down to recent 8 bit formats highlighting the opportunities and the drawbacks of low-precision arithmetic in high-fidelity computational fluid dynamics.