Quantifying performance gains of DirectStorage for the visualisation of time-dependent particle datasets

Abstract Visualisation is an essential tool for analysing unstructured particle data as they are produced, for instance, in molecular dynamics or astrodynamics simulations. Such simulations often comprise multiple time steps, and scientists produce datasets with more and more particles in each step. To handle the steadily increasing size of these simulations, many solutions based on organising the data efficiently or reducing their amount using compression have been proposed over the years. Recently, a new storage API called DirectStorage has been introduced on Xbox consoles and Windows. DirectStorage promises a dramatic reduction of loading times in games by making the transfer from NVMe drives to graphics memory more efficient. That begs the question of whether DirectStorage is also beneficial for visualising time-dependent particle data that have to be streamed from disc to the GPU and whether a potential improvement in throughput enables interactive streaming of frames that traditional APIs cannot handle. For that, we implemented a benchmarking application that supports different streaming methods. We report on the results of an extensive series of tests with varying parameters that influence the streaming performance, which show that the performance of DirectStorage is highly dependent on the choice of various parameters. Graphic Abstract We provide an empirical evaluation for the performance gains to be expected when using the DirectStorage API for rendering dynamic particle data set like the one on the right side. For that, we compare the overlapping DirectStorage-based I/O scheme depicted on at the bottom with traditional methods