Demo: Enabling DNN Inference in the Network Data Plane
Siddhartha, Justin Tan, Rajesh Bansal, Huang Chee Cheun, Yuta Tokusashi, Chong Yew Kwan, Haris Javaid, Mario Baldi · 2023
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.