Performance Analysis of Machine Learning Platforms Using Cloud Native Technology on Edge Devices
Ładowanie...
Data
2023
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
This article presents the results of an experiment performed on a
machine learning edge computing platform composed of a virtualized environment
with a K3s cluster and Kubeflow software. The study aimed to analyze
the effectiveness of executing Kubeflow pipelines for simulated parallel
executions. A benchmarking environment was developed for the experiment
to allow system performance measurements based on parameters, including
the number of pipelines and nodes. The results demonstrate the impact of
the number of cluster nodes on computational time, revealing insights that
could inform future decisions regarding increasing the effectiveness of running
machine learning pipelines on edge devices.
Opis
Słowa kluczowe
machine learning, artificial intelligence, cloud computing, edge computing, internet of things, uczenie maszynowe, sztuczna inteligencja, przetwarzanie w chmurze, przetwarzanie brzegowe, internet rzeczy
Cytowanie
Cłapa K., Grudzień K., Sierszeń A., Performance Analysis of Machine Learning Platforms Using Cloud Native Technology on Edge Devices. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 195-200, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.31.