The evaluation of CUDA performance on the Jetson Nano board for an image binarization task

Febby Purnama Madrin; Maik Rosenberger; Rico Nestler; Paul-Gerald Dittrich; Gunther Notni

doi:10.1117/12.2586650

12 April 2021 The evaluation of CUDA performance on the Jetson Nano board for an image binarization task

Febby Purnama Madrin, Maik Rosenberger, Rico Nestler, Paul-Gerald Dittrich, Gunther Notni

Proceedings Volume 11736, Real-Time Image Processing and Deep Learning 2021; 117360G (2021) https://doi.org/10.1117/12.2586650
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

One of the most preferred platforms or boards for developing 'real-time image-video processing' applications is NVIDIA's Jetson Nano, which is equipped with CUDA that will accelerate the performance. However, there is no research has yet evaluated CUDA performance on the Jetson Nano for Real-Time Image/Video Processing applications. Through this research, an evaluation of the CUDA performance on Jetson Nano will be obtained by running the Thresholding application with and without the CUDA feature. Some of the aspects evaluated from this study are as follows: CPU usage percentage, GPU usage percentage, temperature level, Current Usage on CPU, Current Usage on GPU from the research results, it was found that the CUDA feature does not always provide added value or performance in its use, CUDA will run very effectively when offline (not real-time), but in real-time, the performance with and without CUDA is almost the same.

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Citation Download Citation

Febby Purnama Madrin, Maik Rosenberger, Rico Nestler, Paul-Gerald Dittrich, and Gunther Notni "The evaluation of CUDA performance on the Jetson Nano board for an image binarization task", Proc. SPIE 11736, Real-Time Image Processing and Deep Learning 2021, 117360G (12 April 2021); https://doi.org/10.1117/12.2586650

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