It’s time again for the annual Cray User Group (CUG) conference: this time in Finland! We’ll be contributing to the discussions on how to best use Cray and HPE supercomputers with a paper titled, “Scalable High-Fidelity Simulation of Turbulence With Neko Using Accelerators”. You will also be able to read the paper on our publication page after the conference.
Recent trends and advancements including more diverse and heterogeneous hardware in High-Performance Computing are challenging scientific software developers in their pursuit of good performance and efficient numerical methods. As a result, the well-known maxim “software outlives hardware” may no longer necessarily hold true, and researchers are today forced to re-factor their codes to leverage these powerful new heterogeneous systems. We present Neko – a portable framework for high-fidelity spectral element flow simulations. Unlike prior works, Neko adopts a modern object-oriented Fortran 2008 approach, allowing multi-tier abstractions of the solver stack and facilitating various hardware backends ranging from general-purpose processors, accelerators down to exotic vector processors and Field-Programmable Gate Arrays (FPGAs) via Neko’s device abstraction layer. Focusing on the performance and accuracy of Neko, we show the first direct numerical simulation (DNS) of a Flettner rotor submerged in a turbulent boundary layer, observing excellent agreement of lift with experimental data. Using a mesh with five million spectral elements, which turns into more than a billion unique degrees of freedom, the simulation requires less than three days to complete on accelerated systems compared to weeks on traditional non-accelerated systems. Finally, we present performance measurements on a wide range of accelerated computing platforms, including the EuroHPC pre-exascale system LUMI, where Neko achieves excellent parallel efficiency for a large DNS of turbulent fluid flow using up to 80% of the entire LUMI supercomputer.
Energy consumption constraints for large-scale computing encourage scientists to revise the architecture design of hardware but also applications, algorithms, as well as the underlying working/ storage precision. I will introduce an approach to address the issue of sustainable, but still reliable, computations from the perspective of computer arithmetic tools. We employ VerifiCarlo and its variable precision backend to identify the parts of the code that benefit from smaller floating-point formats. Finally, we show preliminary results on proxies of CFD applications.