SearcharxivSearch

arXiv subjects

Panagiotis Tsoutsanis

Publications and source records attributed to Panagiotis Tsoutsanis.

2 recordsLinked to original sources

Towards Heterogeneous Exascale CFD with a Single Fortran Code Base: OpenMP Target Acceleration of the High-Order Unstructured Solver UCNS3D

Heterogeneous exascale systems are reshaping computational fluid dynamics, yet rewriting mature high-order solvers for accelerators can fragment code bases and weaken reproducibility. We present a single-source OpenMP target modernisation of UCNS3D, a high-order unstructured finite-volume solver for compressible flows. The common CPU/GPU implementation preserves its numerical formulation, Fortran code base, and workflows. Rather than porting isolated kernels, we enable the complete explicit time-advancement path: high-order reconstruction, gradient evaluation, inviscid and viscous fluxes, boundary treatment, halo exchange, and solution update. The implementation uses persistent target data regions, flat run-time arrays, compile-time sizing of temporary storage, explicit local algebra, target-callable routines, and GPU-aware MPI with device-resident buffers. These choices address the irregular stencils, complex data structures, and substantial temporary storage of high-order unstructured CFD. Verification using the compressible Taylor-Green vortex shows CPU and GPU dissipation histories agreeing to machine precision on LUMI and with published reference data. A single-node run on the ARCHER2 GPU platform provides an independent portability check. End-to-end performance is evaluated on fully populated nodes using Taylor-Green vortex, LM1021 sonic-boom, and NASA high-lift CRM benchmarks. Relative to the previous production implementation, the refactored CPU path is 1.27-1.67 times faster, while GPU offload delivers same-node speed-ups of 2.71-4.05 and 84-101 percent strong-scaling efficiency. The results show that standards-based OpenMP provides portable, production-scale acceleration without sacrificing numerical fidelity, CPU performance, or software sustainability.

math-ph

A Hybrid Finite-Volume Reconstruction Framework for Efficient High-Order Shock-Capturing on Unstructured Meshes

In this paper, we present a multi-dimensional, arbitrary-order hybrid reconstruction framework for compressible flows on unstructured meshes. The method combines the efficiency of linear reconstruction with the robustness of high-order non-oscillatory schemes, activated only where needed through a novel a priori detection strategy. By minimising the use of costly CWENOZ and MUSCL reconstructions, the approach substantially reduces computational expense without sacrificing accuracy or stability. The framework blends CWENOZ formulations with the MOOD paradigm and introduces a redesigned Numerical Admissibility Detector that classifies the flow in a single step as smooth, weakly non-smooth, or discontinuous. Smooth regions use high-order linear reconstruction, weakly non-smooth regions use CWENOZ, and discontinuities are treated with second-order MUSCL. This targeted allocation preserves high-order accuracy while ensuring non-oscillatory and stable solutions near shocks. Implemented in the open-source unstructured finite-volume solver UCNS3D, the method supports arbitrary-order reconstruction on mixed-element meshes. Two- and three-dimensional benchmarks confirm the designed accuracy in smooth regions and enhanced robustness in shock-dominated flows. Reduced reliance on nonlinear reconstructions yields up to a 2.5x speed-up over same-order CWENOZ in 3D compressible turbulence simulations, bringing high-order accuracy closer to industrial-scale CFD applications.

math.NA