Concurrent Binary Trees for Large-Scale Game Components

TL;DR

This paper introduces an enhanced concurrent binary tree data-structure for GPU-based adaptive triangulation, enabling large-scale terrain and planetary geometry rendering with improved flexibility and performance.

Contribution

It extends CBT to support arbitrary polygon meshes and uses it as a memory pool for high-level adaptive subdivision on GPUs.

Findings

Supports conforming triangulations of arbitrary polygons.

Achieves triangulation in less than 0.2ms on console hardware.

Enables planetary-scale geometry rendering from coarse meshes.

Abstract

A concurrent binary tree (CBT) is a GPU-friendly data-structure suitable for the generation of bisection based terrain tessellations, i.e., adaptive triangulations over square domains. In this paper, we expand the benefits of this data-structure in two respects. First, we show how to bring bisection based tessellations to arbitrary polygon meshes rather than just squares. Our approach consists of mapping a triangular subdivision primitive, which we refer to as a bisector, to each halfedge of the input mesh. These bisectors can then be subdivided adaptively to produce conforming triangulations solely based on halfedge operators. Second, we alleviate a limitation that restricted the triangulations to low subdivision levels. We do so by using the CBT as a memory pool manager rather than an implicit encoding of the triangulation as done originally. By using a CBT in this way, we concurrently allocate and/or release bisectors during adaptive subdivision using shared GPU memory. We demonstrate the benefits of our improvements by rendering planetary scale geometry out of very coarse meshes. Performance-wise, our triangulation method evaluates in less than 0.2ms on console-level hardware.