Stardust: Accessible and Transparent GPU Support for Information Visualization Rendering

Abstract

Web-based visualization libraries are in wide use, but performance bottlenecks occur when rendering, and especially animating, a large number of graphical marks. While GPU-based rendering can drastically improve performance, that paradigm has a steep learning curve, usually requiring expertise in the computer graphics pipeline and shader programming. In addition, the recent growth of virtual and augmented reality poses a challenge for supporting multiple display environments beyond regular canvases, such as a Head Mounted Display (HMD) and Cave Automatic Virtual Environment (CAVE). In this paper, we introduce a new web-based visualization library called Stardust, which provides a familiar API while leveraging GPU's processing power. Stardust also enables developers to create both 2D and 3D visualizations for diverse display environments using a uniform API. To demonstrate Stardust's expressiveness and portability, we present five example visualizations and a coding playground for four display environments. We also evaluate its performance by comparing it against the standard HTML5 Canvas, D3, and Vega.