high performance computing on graphics processing units: hgpu.org

Direct numerical simulations (DNS) of turbulence have a virtually unbounded need for computing power. To carry out these simulations, software, computer architectures, and algorithms must operate as efficiently as possible to amortize the large computational cost. However, in a computing landscape increasingly incorporating heterogeneous computer systems, changes are necessary. In this thesis, we consider how DNS can be carried out efficiently on upcoming heterogeneous computer systems. This work relates to developing algorithms for upcoming heterogeneous computer architectures, overcoming software challenges associated with large-scale DNS on these platforms, and applying these developments to new flow cases that were previously too costly to carry out. We consider in particular the spectral element method for DNS and evaluate how this method maps to field-programmable gate arrays, graphics processing units, as well as conventional processors. We also consider the issue of trading arithmetic operations for less communication, reducing the cost of solving the linear systems that arise in the spectral element method. Our developments are incorporated into the spectral element framework Neko, enabling Neko to strong-scale efficiently on the largest supercomputers in the world. Finally, we have carried out several DNS such as the simulation of a Flettner rotor in a turbulent boundary layer and simulating Rayleigh-Bénard convection at very high Rayleigh numbers. The developments in this thesis enable the high-fidelity simulation of turbulence on emerging computer systems with high parallel efficiency and performance.