Programmable data planes allow users to define their own data plane algorithms for network
devices including appropriate data plane application programming interfaces (APIs) which …

Traditionally, the data plane has been designed with fixed functions to forward packets using
a small set of protocols. This closed-design paradigm has limited the capability of the …

Distributed deep neural network training (DT) systems are widely deployed in clusters where
the network is shared across multiple tenants, ie, multiple DT jobs. Each DT job computes …

Dataplane languages like P4 enable flexible and efficient packet-processing using domain-
specific primitives such as programmable parsers and match-action tables. Unfortunately …

Writing packet-processing programs for programmable switch pipelines is challenging
because of their all-or-nothing nature: a program either runs at line rate if it can fit within …

The demand for machine learning (ML) has increased significantly in recent decades,
enabling several applications, such as speech recognition, computer vision, and …

Programmable switch hardware makes it possible to move fine-grained control logic inside
the network data plane, improving performance for a wide range of applications. However …

Programmable networks support a wide variety of applications, including access control,
routing, monitoring, caching, and synchronization. As demand for applications grows, so …

This paper presents Aquila, the first practically usable verification system for Alibaba's
production-scale programmable data planes. Aquila addresses four challenges in building a …

Data-plane programmability is now mainstream. As we find more use cases, deployments
need to be able to run multiple packet-processing modules in a single device. These are …