Performance comparison of a signal processing pipeline execution using CPU and GPU
Loading...
Date
Authors
Tomašov, A.
Horváth, T.
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
ORCID
Abstract
The paper compares the execution performance of NumPy and PyTorch mathematical libraries in embedded systems with graphics processing unit (GPU) acceleration. Both frameworks execute a signal processing pipeline from a fiber manipulation detection system, which inspects a signal from a state of polarization analyzer to enhance the security of optical fiber. The performance comparison is evaluated in the NVIDIA Jetson Nano system with 128-core Maxwell GPU. Based on the measured results, the PyTorch library executed on the GPU has performance improvement from 59 % to 84 % on different batch sizes. The results prove the real-time analysis capabilities of such a system with GPU acceleration.
Description
Keywords
Citation
Proceedings I of the 28st Conference STUDENT EEICT 2022: General papers. s. 465-469. ISBN 978-80-214-6029-4
https://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazeni
https://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazeni
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en