Workflow for high-quality visualisation of large-scale CFD simulations by volume rendering

Abstract

High-fidelity CFD simulations can easily generate terabytes to petabytes of resulting data. Post-processing of such data is not an easy task. It holds especially for volume rendering, one of the most illustrative but computationally intensive post-processing techniques.

This paper presents an HPC-ready workflow for post-processing large-scale CFD data computed on unstructured meshes by volume rendering using matured visual effects tools. The workflow consists of five steps: (1) parallel loading of unstructured data into memory, (2) data load-balancing among available resources, (3) re-sampling unstructured data into a regular grid (voxelisation), (4) storing data to OpenVDB format, and (5) final high-quality volume rendering of the (possibly sparse) regular grid in Blender. The workflow is based on open-source libraries, where we have improved all these steps to build an effective and robust approach. Due to parallel loading and appropriate load balancing, our workflow (a) allows loading sequential databases that do not fit into the memory of a single node and (b) significantly outperforms current scientific visualisation tools in voxelisation scalability. Moreover, due to the connection to professional visual effects tools such as Blender, interactive or photo-realistic volume rendering by path tracing, which includes global illumination effects, is allowed.

With the workflow, it is possible to re-sample hundreds of time steps on an unstructured mesh with 1 billion cells (tens of TB of data) to a sparse regular grid with a density of 11 billion voxels and prepare data for interactive visualisation in just a few minutes using thousands of CPU cores.