Building an Accelerated OpenFOAM Proof-of-Concept Application using Modern C++

TL;DR

This paper presents a proof-of-concept OpenFOAM application developed with modern C++ to leverage GPU acceleration, demonstrating improved performance through offloading computations to NVIDIA GPUs using parallel constructs.

Contribution

It introduces a modern C++ based approach for accelerating OpenFOAM applications with GPU offloading, enhancing performance and code simplicity.

Findings

GPU offloading increases OpenFOAM laplacianFoam performance

Single codebase enables multi-core and GPU acceleration

Use of modern C++ constructs simplifies parallel implementation

Abstract

The modern trend in High-Performance Computing (HPC) involves the use of accelerators such as Graphics Processing Units (GPUs) alongside Central Processing Units (CPUs) to speed up numerical operations in various applications. Leading manufacturers such as NVIDIA, Intel, and AMD are constantly advancing these architectures, augmenting them with features such as mixed precision, enhanced memory hierarchies, and specialised accelerator silicon blocks (e.g., Tensor Cores on GPU or AMX/SME engines on CPU) to enhance compute performance. At the same time, significant efforts in software development are aimed at optimizing the use of these innovations, seeking to improve usability and accessibility. This work contributes to the state-of-the-art of OpenFOAM development by presenting a working Proof-Of-Concept application built using modern ISO C++ parallel constructs. This approach, combined with an appropriate compiler runtime stack, like the one provided by the NVIDIA HPC SDK, makes it possible to accelerate well-defined kernels, allowing multi-core execution and GPU offloading using a single codebase. The study demonstrates that it is possible to increase the performance of the OpenFOAM laplacianFoam application by offloading the computations on NVIDIA GPUs using the C++ parallel construct.