FusionRender: Harnessing WebGPU’s Power for Enhanced Graphics Performance on Web Browsers

Weichen Bi, Yun Ma, Yudong Han, Yifan Chen, Deyu Tian, Jiaqi Du

Keywords: Web applications; Graphics; WebGPU; Performance optimization

Abstract: Graphics rendering on the web serves as the cornerstone for numerous web applications. In contrast to the widely employed WebGL, the next-generation web graphics API, WebGPU, demonstrates an enhanced capacity to adapt to modern GPU features, boasting even more significant potential. Nevertheless, our evaluation shows that the current prevalent performance of graphics rendering frameworks based on WebGPU lags behind those built on WebGL. This discrepancy primarily arises from an incomplete alignment with WebGPU's distinctive attributes. The individual rendering of each graphic leads to redundant communication between the CPU and GPU. To enhance the graphics performance on the web, we introduce the FusionRender to harness the power of WebGPU. To mitigate redundant communication, it assigns a unique signature to each object that requires rendering and employs these signatures for grouping, enabling the consolidation of graphic rendering whenever possible. In simulated experiments involving the rendering of multiple objects, FusionRender demonstrates a median rendering performance improvement of 29.3%-122.1% compared to the existing optimal baseline. In real cases with more complex features, performance improvement ranges from 9.4% to 39.7%. Additionally, FusionRender exhibits robust performance across various devices and browsers.

Track: Systems and Infrastructure for Web, Mobile, and WoT

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Submission Number: 465