IGNNITION: fast prototyping of graph neural networks for communication networks
Visualitza/Obre
Cita com:
hdl:2117/361589
Tipus de documentComunicació de congrés
Data publicació2021
EditorAssociation for Computing Machinery (ACM)
Condicions d'accésAccés obert
Tots els drets reservats. Aquesta obra està protegida pels drets de propietat intel·lectual i
industrial corresponents. Sense perjudici de les exempcions legals existents, queda prohibida la seva
reproducció, distribució, comunicació pública o transformació sense l'autorització del titular dels drets
ProjecteNGI-POINTER - NGI Program for Open INTErnet Renovation (EC-H2020-871528)
DISEÑANDO UNA INFRAESTRUCTURA DE RED 5G DEFINIDA MEDIANTE CONOCIMIENTO HACIA LA PROXIMA SOCIEDAD DIGITAL (AEI-TEC2017-90034-C2-1-R)
DISEÑANDO UNA INFRAESTRUCTURA DE RED 5G DEFINIDA MEDIANTE CONOCIMIENTO HACIA LA PROXIMA SOCIEDAD DIGITAL (AEI-TEC2017-90034-C2-1-R)
Abstract
Graph Neural Networks (GNN) have recently exploded in the Machine Learning area as a novel technique for modeling graph-structured data. This makes them especially suitable for applications in the networking field, as communication networks inherently comprise graphs at many levels (e.g., topology, routing, user connections). In this demo, we will present IGNNITION, an open-source framework for fast prototyping of GNNs applied to communication networks. This framework is especially designed for network engineers and/or researchers with limited background on neural network programming. IGNNITION comprises a set of tools and functionalities that eases and accelerates the whole implementation process, from the design of a GNN model, to its training, evaluation, debugging, and integration into larger network applications. In the demo, we will show how a user can implement a complex GNN model applied to network performance modeling (RouteNet), following three simple steps.
CitacióPujol, D. [et al.]. IGNNITION: fast prototyping of graph neural networks for communication networks. A: ACM SIGCOMM Poster and Demo Sessions. "Proceedings of the 2021 SIGCOMM'21 poster and demo sessions: August 23-27, 2021 virtual event, USA". New York: Association for Computing Machinery (ACM), 2021, p. 71-73. ISBN 978-1-4503-8629-6. DOI 10.1145/3472716.3472853.
ISBN978-1-4503-8629-6
Versió de l'editorhttps://dl.acm.org/doi/abs/10.1145/3472716.3472853
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Demo_SIGCOMM_21 (8).pdf | 352,0Kb | Visualitza/Obre |