Performance comparison of a signal processing pipeline execution using CPU and GPU

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but.event.date26.04.2022cs
but.event.titleSTUDENT EEICT 2022cs
dc.contributor.authorTomašov, A.
dc.contributor.authorHorváth, T.
dc.date.accessioned2023-04-25T10:17:10Z
dc.date.available2023-04-25T10:17:10Z
dc.date.issued2022cs
dc.description.abstractThe 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.en
dc.formattextcs
dc.format.extent465-469cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings I of the 28st Conference STUDENT EEICT 2022: General papers. s. 465-469. ISBN 978-80-214-6029-4cs
dc.identifier.isbn978-80-214-6029-4
dc.identifier.urihttp://hdl.handle.net/11012/209386
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings I of the 28st Conference STUDENT EEICT 2022: General papersen
dc.relation.urihttps://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazenics
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectFiber Optics Securityen
dc.subjectGPUen
dc.subjectNVIDIA Jetson Nanoen
dc.subjectPyTorchen
dc.subjectSignal Processing Accelerationen
dc.titlePerformance comparison of a signal processing pipeline execution using CPU and GPUen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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