P4 Developer Days - SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate
2026-03-19 08:00 - 09:00 UTC
Register to attend this P4 Developer Days webinar, “SpliDT: Partitioned Decision Trees for Scalable Stateful Inference at Line Rate”
March 19 at 11 am ET/4 pm CET
Slides (PDF) || Watch Recording

Abstract
Machine learning is increasingly used in programmable data planes, such as switches and smartNICs, to enable real-time traffic analysis and security monitoring at line rate. Decision trees (DTs) are particularly well-suited for these tasks due to their interpretability and compatibility with the Reconfigurable Match-Action Table (RMT) architecture. However, current DT implementations require collecting all features upfront, which limits scalability and accuracy due to constrained data plane resources. This paper introduces SpliDT, a scalable framework that reimagines DT deployment as a partitioned inference problem over a sliding window of packets.
By dividing inference into sequential subtrees—each using its own set of top-k features—SpliDT supports more stateful features without exceeding hardware limits. An in-band control channel manages transitions between subtrees and reuses match keys and registers across partitions, implemented using P4 for packet recirculation and control-plane coordination. This design allows physical resources to be shared efficiently while maintaining line-rate processing. To maximize accuracy and scalability, SpliDT employs a custom training and design-space-exploration (DSE) workflow that jointly optimizes feature allocation, tree depth, and partitioning. Evaluations show that SpliDT supports up to 5x more features, scales to millions of flows, and outperforms baselines, with low overhead and minimal time-to-detection (TTD).

Speaker
Murayyiam Parvez is a Ph.D. candidate in the Department of Computer Science at Purdue University, advised by Professor Muhammad Shahbaz and Professor Sonia Fahmy. Her research focuses on designing the next generation of hybrid software–hardware abstractions and architectures for emerging network security and machine learning applications, with an emphasis on leveraging programmable switches to enable high-performance, in-network intelligence.

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P4 Developer Days – OpenDesc: Describing NIC-Host Interfaces
2026-04-30 08:00 - 09:00 (America/Vancouver)
Register to attend this P4 Developer Day webinar on April 30 at 11 am ET/5 pm CET
OpenDesc: Describing NIC-Host Interfaces

Abstract
Modern NIC hardware is increasingly expressive, yet host software remains shackled to static, device-specific descriptors and ad-hoc glue layers. We present OpenDesc, a framework that leverages P4 to define the interface between host and NIC. By treating software intent and hardware capabilities as negotiable P4 programs, OpenDesc automatically compiles minimalist, application-specific driver datapaths for metadata. This approach eliminates the “lowest common denominator” bottleneck, enabling seamless metadata exchange and hardware-software co-design across heterogeneous NIC architectures.
Speaker
Seyyidahmed is a systems researcher at imec. His research interests include the co-design of programmable hardware and high-performance networking stacks, with a focus on improving the flexibility, programmability, and efficiency of modern networked systems.

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P4 Developer Days – P4TC Provisioning And Runtime Control API
2026-05-13 08:00 - 09:00 (America/Vancouver)
Register to attend this P4 Developer Day webinar on May 13 at 11 am ET/5 pm CET
P4TC Provisioning And Runtime Control API

Abstract
The P4TC Control APIs consist of two primary interfaces built on the netlink framework: one for provisioning P4 program manifestations in the Linux kernel and another for managing the P4 runtime. This talk focuses on the P4TC runtime, which employs P4 annotations to link datapath constructs with the control plane. These annotations are converted by the compiler into a JSON format, allowing runtime control applications to introspect both control and data path constructs.
Architecturally, the P4TC runtime API is inspired by the REST paradigm, employing resource-oriented paths as nouns and a refined set of verbs. The verbs follow CRUD (Create, Read, Update, and Delete) principles and include specialized extensions for event publish-subscribe functionality. By using “paths” to target specific datapath objects, the API remains agnostic regarding the nature of those objects – implying a control application does not need to change for multitudes of P4 programs.
Speaker
For more than twenty years, Jamal Hadi Salim has been a leader in the evolution of networking and Software-Defined Networking (SDN). He is a major contributor to the Linux kernel networking subsystem and the current maintainer of the Traffic Control (tc) subsystem. Currently, he leads the P4TC initiative, which enables P4 programs to run directly within the Linux kernel.
His previous leadership roles include serving as the chair for the IETF SDN working group on Forwarding and Control Element Separation (ForCES). During his tenure, he developed a ForCES implementation used in large-scale telecommunications and authored multiple SDN standards. Currently, Jamal is concentrating on the performance of AI/ML, with a specific emphasis on networking protocols and infrastructure.

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Further Reading
Want to learn more about P4TC? Check out their blog

P4 Developer Days – EdgeP4: In-Network Edge Intelligence for a Tactile Cyber-Physical System Testbed Across Cities
2026-05-20 08:00 - 09:00 (America/Vancouver)
Register to attend this P4 Developer Day webinar on May 20 at 11 am ET/5 pm CET
EdgeP4: In-Network Edge Intelligence for a Tactile Cyber-Physical System Testbed Across Cities

Abstract
Tactile Internet based operations, e.g., telesurgery, rely on the human operator for end-to-end closed loop control to achieve accuracy. While feedback and control are subject to network latency and packet loss, critical operations such as pose correction, fiducial marking, tremor reduction, etc. are tasks that should be carried out automatically and thus dispensing with these feedback signals from traversing the network to the other end. We designed two edge intelligence algorithms hosted at P4 programmable end switches placed 400 km apart. These algorithms locally compute and command corrective signals. We implement these algorithms entirely on the data plane on Netronome Agilio SmartNICs. “pose correction” is placed at the edge switch connected to an industrial robot gripping a tool.
The round trip between transmitting force sensor array readings to the edge switch and receiving correct tip coordinates at the robot is shown to be less than 100µs. “tremor suppression” is placed at the edge switch connected to the operator. It suppresses physiological tremors, which improves the application’s performance and also reduces the network load up to 99.9%. Our EdgeP4 framework allows edge intelligence modules to seamlessly switch between the algorithms based on the tasks being executed by devices connected to their ports.

Speaker
Deepak Choudhary is currently a master’s student and a research assistant at Aalto University, Finland. His research interests primarily lie in Systems and Networking, specifically in software-defined networking and programmable data planes. Previously, he spent 2.5 years as a research assistant at the Indian Institute of Science (IISc). His work there focused on developing a P4-programmable Time-Sensitive Networking (TSN) switch and testing them on wide-area network testbeds.

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