Interactive Visualization of Terascale Data in the Browser: Fact or Fiction?

Information visualization applications have become ubiquitous, in no small part thanks to the ease of wide distribution and deployment to users enabled by the web browser. Scientific visualization applications, relying on native code libraries and parallel processing, have been less suited to such widespread distribution, as browsers do not provide the required libraries or compute capabilities. In this paper, we revisit this gap in visualization technologies and explore how new web technologies, WebAssembly and WebGPU, can be used to deploy powerful visualization solutions for large-scale scientific data in the browser. In particular, we evaluate the programming effort required to bring scientific visualization applications to the browser through these technologies and assess their competitiveness against classic native solutions. As a main example, we present a new GPU-driven isosurface extraction method for block-compressed data sets, that is suitable for interactive isosurface computation on large volumes in resource-constrained environments, such as the browser. We conclude that web browsers are on the verge of becoming a competitive platform for even the most demanding scientific visualization tasks, such as interactive visualization of isosurfaces from a 1TB DNS simulation. We call on researchers and developers to consider investing in a community software stack to ease use of these upcoming browser features to bring accessible scientific visualization to the browser

CUDA-based Triangulations of Convolution Molecular Surfaces

Computing molecular surfaces is important to measure areas and volumes of molecules, as well as to infer useful information about interactions with other molecules. Over the years many algorithms have been developed to triangulate and to render molecular surfaces. However, triangulation algorithms usually are very expensive in terms of memory storage and time performance, and thus far from real-time performance. Fortunately, the massive computational power of the new generation of low-cost GPUs opens up an opportunity window to solve these problems: real-time performance and cheap computing commodities. This paper just presents a GPU-based algorithm to speed up the triangulation and rendering of molecular surfaces using CUDA. Our triangulation algorithm for molecular surfaces is based on a multi-threaded, parallel version of the Marching Cubes (MC) algorithm. However, the input of our algorithm is not the volume dataset of a given molecule as usual for Marching Cubes, but the atom centers provided by the PDB file of such a molecule. We also carry out a study that compares a serial version (CPU) and a parallel version (GPU) of the MC algorithm in triangulating molecular surfaces as a way to understand how real-time rendering of molecular surfaces can be achieved in the future