Year
Month
(Conference Paper) IGNNITION: fast prototyping of graph neural networks for communication networks
David Pujol-Perich ¹, José Suárez-Varela ¹, Miquel Ferriol-Galmés ¹, Bo Wu ², Shihan Xiao ², Xiangle Cheng ², Albert Cabellos-Aparicio ¹, Pere Barlet-Ros ¹
¹ Barcelona Neural Networking center, Universitat Politècnica de Catalunya, Spain
² Network Technology Lab., Huawei Technologies Co., Ltd.
华为技术有限公司网络技术实验室
SIGCOMM '21: Proceedings of the SIGCOMM '21 Poster and Demo Sessions, 2021-08-23
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.
IGNNITION: fast prototyping of graph neural networks for communication networks_1
IGNNITION: fast prototyping of graph neural networks for communication networks_2
  • High-resolution tumor marker detection based on microwave photonics demodulated dual wavelength fiber laser sensor
  • Jie Hu, Weihao Lin, Liyang Shao, Chenlong Xue, Fang Zhao, Dongrui Xiao, Yang Ran, Yue Meng, Panpan He, Zhiguang Yu, Jinna Chen, Perry Ping Shum
  • Opto-Electronic Advances
  • 2024-12-16
  • High performance laser induced plasma assisted ablation by GHz burst mode femtosecond pulses
  • Jingbo Yin, Yulong Zhao, Minghui Hong
  • Opto-Electronic Advances
  • 2024-12-16
  • Sequential harmonic spin–orbit angular momentum generation in nonlinear optical crystals
  • Yutao Tang, Zixian Hu, Junhong Deng, Kingfai Li, Guixin Li
  • Opto-Electronic Advances
  • 2024-12-16
  • Design, setup, and facilitation of the speckle structured illumination endoscopic system
  • Elizabeth Abraham, Zhaowei Liu
  • Opto-Electronic Science
  • 2024-12-13
  • Ultra-high-Q photonic crystal nanobeam cavity for etchless lithium niobate on insulator (LNOI) platform
  • Zhi Jiang, Cizhe Fang, Xu Ran, Yu Gao, Ruiqing Wang, Jianguo Wang, Danyang Yao, Xuetao Gan, Yan Liu, Yue Hao, Genquan Han
  • Opto-Electronic Advances
  • 2024-10-31
  • Advanced biological imaging techniques based on metasurfaces
  • Yongjae Jo, Hyemi Park, Hyeyoung Yoon, Inki Kim
  • Opto-Electronic Advances
  • 2024-10-31
  • Orthogonal matrix of polarization combinations: concept and application to multichannel holographic recording
  • Shujun Zheng, Jiaren Tan, Hongjie Liu, Xiao Lin, Yusuke Saita, Takanori Nomura, Xiaodi Tan
  • Opto-Electronic Advances
  • 2024-10-23
  • Streamlined photonic reservoir computer with augmented memory capabilities
  • Changdi Zhou, Yu Huang, Yigong Yang, Deyu Cai, Pei Zhou, Kuenyao Lau, Nianqiang Li, Xiaofeng Li
  • Opto-Electronic Advances
  • 2024-10-22
  • High-precision multi-focus laser sculpting of microstructured glass
  • Kang Xu, Peilin Huang, Lingyu Huang, Li Yao, Zongyao Li, Jiantao Chen, Li Zhang, Shaolin Xu
  • Opto-Electronic Advances
  • 2024-10-09
  • Multi-physical field null medium: new solutions for the simultaneous control of EM waves and heat flow
  • Sailing He, Ruili Zhang, Junbo Liang
  • Opto-Electronic Advances
  • 2024-09-30
  • Adaptive decentralized AI scheme for signal recognition of distributed sensor systems
  • Shixiong Zhang, Hao Li, Cunzheng Fan, Zhichao Zeng, Chao Xiong, Jie Wu, Zhijun Yan, Deming Liu, Qizhen Sun
  • Opto-Electronic Advances
  • 2024-09-29
  • Data-driven polarimetric approaches fuel computational imaging expansion
  • Sylvain Gigan
  • Opto-Electronic Advances
  • 2024-09-28



  • From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network                                Adversarial Reciprocal Points Learning for Open Set Recognition
    About
    |
    Contact
    |
    Copyright © PubCard