DPDK Summit 2026

In this session, we will explore a use case where PCI endpoint card is utilized to offload cryptographic operations from the host machine. The buffers for these operations are transferred to the PCI card via the virtio/ethernet interface between the host and the endpoint over PCI. We will discuss two distinct approaches to manage crypto operations.

Approach 1: Standard Virtio-Crypto Interface - DPDK/kernel virtio-crypto device is used to establish crypto sessions and transmit data across the PCI endpoint. The endpoint performs cryptographic operations and returns processed data to the virtio-crypto device. The application running on the endpoint translates the virtio-crypto sessions and processes the data using the DPDK crypto device on the endpoint, subsequently sending the processed data back to the host.
Approach 2: LiquidCrypto - Due to limited virtio-crypto offload capabilities, second approach is proposed. This method utilizes the DPDK ethernet SDP interface between the host and endpoint for fast path transport and the kernel SDP interface for slow path and management of the PCI card. The sample applications and the interface library are open-source and available on GitHub.

As network speeds increase, relying on hardware offloading via rte_flow becomes essential. However, the implementation of these APIs varies significantly across vendors. This talk shares findings from an ongoing exploration of NIC performance (NVIDIA, Intel or DYNANIC), with a primary focus on the capabilities and limitations of hardware-offloaded packet filtering using the DPDK rte_flow API. While standard throughput metrics are important, this session moves beyond basic performance to explore the behavior of NICs under stress and in ambiguous scenarios that are often overlooked in standard datasheets.

Doing packet capture in a DPDK application leads to several technical issues. Packet capture needs to be fast, transparent and be easy to use. This talk will cover the different solutions and how they can be improved in the future.

Over the past year, the Tech Board has been reviewing how to integrate LLMs into the CI workflow to enact an assisted review cycle for patches. This work has looked at various aspects of adding an AI review assistant to the process that can help maintainers and developers spot difficult to reach issues. The results of the trial-and-error testing have lead to a new AI assistant that helps to review patches and series.
In this talk, we'll cover the various roads we took for analysis, AI review infrastructure that lives in the tree, the policy around getting an LLM review of patches, and future work.