Boosting performance of computer vision applications through embedded GPUs on the edge
Fuente:
arXiv
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866911246933032960 |
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| author | Rossi, Fabio Diniz |
| author_facet | Rossi, Fabio Diniz |
| contents | Computer vision applications, especially those using augmented reality technology, are becoming quite popular in mobile devices. However, this type of application is known as presenting significant demands regarding resources. In order to enable its utilization in devices with more modest resources, edge computing can be used to offload certain high intensive tasks. Still, edge computing is usually composed of devices with limited capacity, which may impact in users quality of experience when using computer vision applications. This work proposes the use of embedded devices with graphics processing units (GPUs) to overcome such limitation. Experiments performed shown that GPUs can attain a performance gain when compared to using only CPUs, which guarantee a better experience to users using such kind of application. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_01129 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Boosting performance of computer vision applications through embedded GPUs on the edge Rossi, Fabio Diniz Computer Vision and Pattern Recognition Distributed, Parallel, and Cluster Computing Computer vision applications, especially those using augmented reality technology, are becoming quite popular in mobile devices. However, this type of application is known as presenting significant demands regarding resources. In order to enable its utilization in devices with more modest resources, edge computing can be used to offload certain high intensive tasks. Still, edge computing is usually composed of devices with limited capacity, which may impact in users quality of experience when using computer vision applications. This work proposes the use of embedded devices with graphics processing units (GPUs) to overcome such limitation. Experiments performed shown that GPUs can attain a performance gain when compared to using only CPUs, which guarantee a better experience to users using such kind of application. |
| title | Boosting performance of computer vision applications through embedded GPUs on the edge |
| topic | Computer Vision and Pattern Recognition Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2511.01129 |