Date of Award
5-2022
Document Type
Thesis open access
Department
Computer Science
First Advisor
Mark C Lewis
Second Advisor
Britton Horn
Third Advisor
Matthew A Hibbs
Abstract
This work encapsulates three explorations into different implementations of distributed ray tracing, that is to say, ray tracing that has been distributed across multiple machines. Our goals lie in the rendering of scenes with more geometry than can fit within the memory of a single computer, so we focus on the distribution of memory. Ultimately, this work discusses a Spark standard (or classical) distributed ray tracer, a Spark photometric distributed ray tracer, and a single-machine Akka Typed photometric ray tracer with some basis for future distribution. Individual timing results for each ray tracer are included, but they cannot be compared due to differences in their generation. Qualitative comparisons between the ray tracers and their approaches are made, and recommendations are given to future researchers in this niche.
Recommended Citation
Weisenberger, Connor W., "Explorations in Distributed Ray Tracing and Photometry of Large Scenes" (2022). Computer Science Honors Theses. 66.
https://digitalcommons.trinity.edu/compsci_honors/66
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.