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Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments
Cluster computing has attracted much attention as an effective way of solving large-scale problems. However, only a few attempts have been made to explore mobile computing clusters that can be easily built using commodity smartphones and tablets. To investigate the possibility of mobile cluster-base...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8778953/ https://www.ncbi.nlm.nih.gov/pubmed/35062452 http://dx.doi.org/10.3390/s22020491 |
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author | Seo, Woong Park, Sanghun Ihm, Insung |
author_facet | Seo, Woong Park, Sanghun Ihm, Insung |
author_sort | Seo, Woong |
collection | PubMed |
description | Cluster computing has attracted much attention as an effective way of solving large-scale problems. However, only a few attempts have been made to explore mobile computing clusters that can be easily built using commodity smartphones and tablets. To investigate the possibility of mobile cluster-based rendering of large datasets, we developed a mobile GPU ray tracer that renders nontrivial 3D scenes with many millions of triangles at an interactive frame rate on a small-scale mobile cluster. To cope with the limited processing power and memory space, we first present an effective 3D scene representation scheme suitable for mobile GPU rendering. Then, to avoid performance impairment caused by the high latency and low bandwidth of mobile networks, we propose using a static load balancing strategy, which we found to be more appropriate for the vulnerable mobile clustering environment than a dynamic strategy. Our mobile distributed rendering system achieved a few frames per second when ray tracing 1024 × 1024 images, using only 16 low-end smartphones, for large 3D scenes, some with more than 10 million triangles. Through a conceptual demonstration, we also show that the presented rendering scheme can be effectively explored for augmenting real scene images, captured or perceived by augmented and mixed reality devices, with high quality ray-traced images. |
format | Online Article Text |
id | pubmed-8778953 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87789532022-01-22 Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments Seo, Woong Park, Sanghun Ihm, Insung Sensors (Basel) Article Cluster computing has attracted much attention as an effective way of solving large-scale problems. However, only a few attempts have been made to explore mobile computing clusters that can be easily built using commodity smartphones and tablets. To investigate the possibility of mobile cluster-based rendering of large datasets, we developed a mobile GPU ray tracer that renders nontrivial 3D scenes with many millions of triangles at an interactive frame rate on a small-scale mobile cluster. To cope with the limited processing power and memory space, we first present an effective 3D scene representation scheme suitable for mobile GPU rendering. Then, to avoid performance impairment caused by the high latency and low bandwidth of mobile networks, we propose using a static load balancing strategy, which we found to be more appropriate for the vulnerable mobile clustering environment than a dynamic strategy. Our mobile distributed rendering system achieved a few frames per second when ray tracing 1024 × 1024 images, using only 16 low-end smartphones, for large 3D scenes, some with more than 10 million triangles. Through a conceptual demonstration, we also show that the presented rendering scheme can be effectively explored for augmenting real scene images, captured or perceived by augmented and mixed reality devices, with high quality ray-traced images. MDPI 2022-01-10 /pmc/articles/PMC8778953/ /pubmed/35062452 http://dx.doi.org/10.3390/s22020491 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Seo, Woong Park, Sanghun Ihm, Insung Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments |
title | Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments |
title_full | Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments |
title_fullStr | Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments |
title_full_unstemmed | Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments |
title_short | Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments |
title_sort | efficient ray tracing of large 3d scenes for mobile distributed computing environments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8778953/ https://www.ncbi.nlm.nih.gov/pubmed/35062452 http://dx.doi.org/10.3390/s22020491 |
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