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Importance-Based Ray Strategies for Dynamic Diffuse Global Illumination

Authors:

Jerry ZhangAuthors Info & Claims

Proceedings of the ACM on Computer Graphics and Interactive Techniques, Volume 6, Issue 1

Article No.: 9, Pages 1 - 20

https://doi.org/10.1145/3585500

Published: 16 May 2023 Publication History

Abstract

In this paper, we propose a first and efficient ray allocation technique for Dynamic Diffuse Global Illumination (DDGI) using Multiple Importance Sampling (MIS). Our technique, IS-DDGI, extends DDGI by incorporating a set of importance-based ray strategies that analyze, allocate, and manage ray resources on the GPU. We combine these strategies with an adaptive historical and temporal frame-to-frame analysis for an effective reuse of information and a set of GPU-based optimizations for speeding up ray allocation and reducing memory bandwidth. Our IS-DDGI achieves similar visual quality to DDGI with a speedup of 1.27x to 2.47x in total DDGI time and 3.29x to 6.64x in probes ray tracing time over previous technique [Majercik et al. 2021]. Most speedup of IS-DDGI comes from probes ray tracing speedup.

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Index Terms

Importance-Based Ray Strategies for Dynamic Diffuse Global Illumination
1. Computing methodologies
  1. Computer graphics
    1. Rendering
      1. Ray tracing

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cover image Proceedings of the ACM on Computer Graphics and Interactive Techniques

Proceedings of the ACM on Computer Graphics and Interactive Techniques Volume 6, Issue 1

May 2023

287 pages

EISSN:2577-6193

DOI:10.1145/3597486

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Copyright © 2023 ACM.

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Published: 16 May 2023

Published in PACMCGIT Volume 6, Issue 1

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liu: Supplemental movie, appendix, image and software files for, Importance-Based Ray Strategies for Dynamic Diffuse Global Illumination https://dl.acm.org/doi/10.1145/3585500#liu.zip

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https://dl.acm.org/doi/10.1145/3700595
Bian HGuo BLiu SDing YGao SYu Z(2024)UbiHR: Resource-efficient Long-range Heart Rate Sensing on Ubiquitous DevicesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36997718:4(1-26)Online publication date: 21-Nov-2024
https://dl.acm.org/doi/10.1145/3699771
Fang CLiu SZhou ZGuo BTang JMa KYu ZShu YLiu JTan RHe YChen J(2024)AdaShadow: Responsive Test-time Model Adaptation in Non-stationary Mobile EnvironmentsProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699339(295-308)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3666025.3699339
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