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You are here: Home / Videos / Jericho4: Enabling Distributed AI Computing Across Data Centers with Broadcom

Jericho4: Enabling Distributed AI Computing Across Data Centers with Broadcom



AI Infrastructure Field Day 3


This video is part of the appearance, “Broadcom presents at AI Infrastructure Field Day 3“. It was recorded as part of AI Infrastructure Field Day 3 at 8:00-9:30 on September 10, 2025.


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Jericho4 – Ethernet Fabric Router is a purpose-built platform for the next generation of distributed AI infrastructure. In this session, we will examine how Jericho4 pushes beyond traditional scaling limits, delivering unmatched bandwidth, integrated security, and true lossless performance—while interconnecting more than one million XPUs across multiple data centers.

The presentation discusses the Jericho 4 solution for scaling AI infrastructure across data centers. Current limitations in power and space capacity necessitate interconnecting smaller data centers via high-speed networks. Jericho 4 addresses the growing challenges of load balancing, congestion control, traffic management, and security at scale by offering four key features. First, it allows building a single system with 36K ports, acting as a single, non-blocking routing domain. Second, it provides high bandwidth with hyper ports (3.2T), a native solution for the large data flows characteristic of AI workloads. Third, its embedded deep buffer supports lossless RDMA interconnections over distances exceeding 100 kilometers. Finally, Jericho 4 has embedded security engines to enable security without impacting performance.

The Jericho 4 family offers various derivatives to suit different deployment scenarios, including modular and centralized systems. The architecture supports scaling as a single system through various form factors, from compact boxes to disaggregated chassis, and further scaling across a fabric. Hyper ports improve link utilization by avoiding hashing and collisions, leading to reduced training times. The deep buffer handles the bursty nature of AI workloads, minimizing congestion and ensuring lossless data transmission even over long distances. The embedded security engine addresses security concerns by enabling point-to-point MACsec and end-to-end IPsec with no performance impact.

Personnel: Henry Wu

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