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short-paper

Demo: Enabling DNN Inference in the Network Data Plane

Authors:

Huang Chee Cheun,

Yuta Tokusashi,

Chong Yew Kwan,

Mario BaldiAuthors Info & Claims

EuroP4 '23: Proceedings of the 6th on European P4 Workshop

Pages 65 - 68

https://doi.org/10.1145/3630047.3630191

Published: 06 December 2023 Publication History

Abstract

Advancements in programmable packet processing technologies have fostered innovation across a range of networking applications. Integration of deep neural networks (DNN) in the network data plane, however, has remained largely unaddressed due to the high compute requirements of the underlying algebraic kernels. In this paper, we show how P4 packet processing pipelines can be augmented with DNN inference engines on devices readily available in the market today. We share a network security case study, where we train a DNN-based anomaly detector that classifies active traffic flows as either malicious or benign using per-packet inference. Our implementation runs on an AMD Alveo\textsuperscriptTM U250 FPGA accelerator card, and is capable of servicing network traffic of up to \approx~98~Mpps on 100~GbpE links.

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Cited By

McHale LGratz PSprintson A(2024)Flow Correlator: A Flow Table Cache Management Strategy2024 33rd International Conference on Computer Communications and Networks (ICCCN)10.1109/ICCCN61486.2024.10637657(1-9)Online publication date: 29-Jul-2024
https://doi.org/10.1109/ICCCN61486.2024.10637657
Kumar AJaison Vincent Solomon JAN RRaghupatruni MBodas ASable NChitti DPatnaik SPadubidri S(2024)Regulus: Programmable, high performance network data plane inferencing on FPGA2024 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)10.1109/CONECCT62155.2024.10677156(1-6)Online publication date: 12-Jul-2024
https://doi.org/10.1109/CONECCT62155.2024.10677156

Index Terms

Demo: Enabling DNN Inference in the Network Data Plane
1. Computer systems organization
  1. Architectures
    1. Other architectures

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Information & Contributors

Information

Published In

cover image ACM Conferences

EuroP4 '23: Proceedings of the 6th on European P4 Workshop

December 2023

74 pages

ISBN:9798400704468

DOI:10.1145/3630047

General Chairs:
Fernando Ramos
University of Lisbon, PT
,
Muhammad Shahbaz
Purdue University, US
,
Program Chairs:
Vladimir Gurevich
P4ica, US
,
Salvatore Signorello
Telefonica Research, ES

Copyright © 2023 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGCOMM: ACM Special Interest Group on Data Communication

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 December 2023

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Short-paper

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CoNEXT 2023

Sponsor:

SIGCOMM

CoNEXT 2023: The 19th International Conference on emerging Networking EXperiments and Technologies

December 8, 2023

Paris, France

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Cited By

McHale LGratz PSprintson A(2024)Flow Correlator: A Flow Table Cache Management Strategy2024 33rd International Conference on Computer Communications and Networks (ICCCN)10.1109/ICCCN61486.2024.10637657(1-9)Online publication date: 29-Jul-2024
https://doi.org/10.1109/ICCCN61486.2024.10637657
Kumar AJaison Vincent Solomon JAN RRaghupatruni MBodas ASable NChitti DPatnaik SPadubidri S(2024)Regulus: Programmable, high performance network data plane inferencing on FPGA2024 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)10.1109/CONECCT62155.2024.10677156(1-6)Online publication date: 12-Jul-2024
https://doi.org/10.1109/CONECCT62155.2024.10677156

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