Repurposing GPU Ray Tracing Architecture for Accelerating Irregular Programs

Abstract

With the near-ending of Moore’s law and ever increasing demand for compute power, Domain-Specific Accelerators (DSA) have become a default choice for high-performance workloads. However, developing a custom DSA is an extremely time-consuming and expensive process that only a few organizations can afford. This thesis shows how to repurpose GPU Ray Tracing Architecture, a DSA built for rendering in graphics applications, for non-rendering applications such as k-nearest neighbor search, collision detection in DEM simulations, and spatial queries. The main purpose of Ray Tracing Architecture is to compute intersections between rays and objects in a scene using Euclidean distance. Even though this hardware is capable of computing only the Euclidean distance, Arkade introduces two reductions to compute neighbors according to other distances such as L^p norms and Cosine distance. Mochi and S-ray further show how to reinterpret ray-object intersection tests to compute intersections between objects for collision detection and spatial query execution.