OSS + ELC EU 2026

Processing large volumes of sensor data (e.g. Cameras, IMUs, Radar, etc.) on embedded hardware for real-time machine learning inference requires two critical performance metrics: high throughput and minimal latency.

Remote Direct Memory Access (RDMA) which originated in high-performance computing and cloud datacenters was designed for this use case . By enabling direct host-to-host memory transfers without kernel or CPU intervention, RDMA delivers throughputs exceeding 100 Gbps with microsecond-level latency.

In this talk, we present a complete, open-source sensor acquisition pipeline that brings RDMA to an embedded device. We demonstrate how camera data is acquired on an AMD Kria KR260, packetized into RDMA frames entirely within the FPGA fabric, and transmitted over Ethernet to a Jetson AGX Orin platform. The goal of this talk is that attendees will leave with a practical understanding of RDMA’s benefits in the embedded sector and have access to a powerful, open-source tool for high-performance data transfer.