high performance computing on graphics processing units: hgpu.org

For real-time applications (dynamic data-driven applications systems like computer-assisted surgery, command and control, etc.), it is necessary to design fast or strongly-accelerated computational approaches. Reduced-order modeling (ROM) is a candidate methodology that summarizes all the parameter-dependent PDE solutions into an easy-to-compute condensed form. ROM usually requires an offline learning process that returns the essential components of the solutions. However, it is known that ROM methodology is not suitable for all problems, especially problems with a large Kolmogorov $n$-width, like for example dynamical problems involving a continuous multiscale spectrum (like turbulence). In this case, direct simulation is needed and one has to find acceleration strategies. Graphics Processing units (GPU) are a cheap but relevant way to parallelize computations on thousands of cores leading to speedups of order 200 for some algorithms. This paper talks about real-time CFD computations allowing for real time visualization and flow interaction.