Purdue University Graduate School
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Repurposing GPU Ray Tracing Architecture for Accelerating Irregular Programs

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thesis
posted on 2025-07-23, 14:05 authored by Durga Keerthi MandarapuDurga Keerthi Mandarapu
<p dir="ltr">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.</p>

Funding

NSF CCF-1908504, CCF-1919197 and CCF-2216978

History

Degree Type

  • Doctor of Philosophy

Department

  • Computer Science

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Milind Kulkarni

Additional Committee Member 2

Walid Aref

Additional Committee Member 3

Benjamin Delaware

Additional Committee Member 4

Changhee Jung

Additional Committee Member 5

Jianguo Wang