DPDK Summit 2026

DPDK transformed wired networking by giving host software direct control over packet processing. This talk makes the case that the same approach should be applied to 802.11 wireless.

Wi-Fi’s real behavior—contention, TXOP scheduling, A-MPDU aggregation, rate adaptation, and retries—is hidden below the 802.3 interface inside firmware and hardware state machines. This prevents per-packet observability and programmable control.

We propose a Wi-Fi Poll Mode Driver model that operates natively on 802.11 frames, exposing aggregation and retry behavior as first-class metadata and accepting explicit transmission parameters (MCS/NSS/BW, TXOP limits, retry policy). With this interface, a DPDK application can coordinate microsecond-scale MAC scheduling with millisecond-scale ECN/AQM control.

We outline the required PMD interface, metadata surface, and driver hooks needed to bring software-defined control to wireless networking.

Overview of GFNI based Toeplitz hash implementation

Physical AI systems demand ultra‑low‑latency transport of rich sensor data from the edge to centralized AI compute. This talk showcases a DPDK‑based sensor bridge using NXP i.MX processors as NVIDIA Holoscan Sensor Bridge endpoints, delivering deterministic, zero‑copy perception pipelines. It highlights how DPDK unlocks a new class of real‑time workloads for robotics, industrial vision, and Physical AI.