Rethinking Edge AI Interconnects: Why Multi-Protocol Is the New Standard

By Joe Chen

November 6, 2025

Modern compute systems have evolved beyond reliance on a single dominant interface. Today, they're increasingly defined by their ability to support multiple high-speed protocols concurrently—including PCIe, Ethernet, and others. This shift toward multi-protocol capability is fundamentally reshaping how we architect intelligent edge AI systems, especially as inferencing workloads grow more distributed, data-intensive, and latency-sensitive.

Autonomous Systems Demand Real-Time Edge AI—and Smarter Interconnects

Autonomous platforms, extending from vehicles to industrial robots, rely on real-time AI inferencing to make split-second, accurate decisions. These systems must rapidly process massive volumes of sensor data, run complex models on AI accelerators, and coordinate with central compute units (CCUs)—all under tight latency and power constraints.

To meet these demands, concurrent multi-protocol support is no longer a luxury—it's a necessity. A multi-protocol PHY that enables PCIe 5.0 and 25G Ethernet to operate simultaneously delivers the high-speed, low-latency connectivity required across the entire edge AI stack.

While newer standards, like PCIe 6.0/7.0 and high-speed Ethernet, are advancing rapidly, they often introduce higher power consumption, cost, and integration complexity—making them better suited for hyperscale data centers than edge environments. In contrast, PCIe 5.0 and 25G Ethernet strike the right balance of bandwidth, efficiency, and ecosystem maturity, making them ideal for real-time, production-ready edge deployments.

This concurrent capability unlocks several key benefits:

• Parallel Data Paths for Maximum Throughput: Supporting both protocols concurrently allows sensor data ingestion and compute offloading to happen in parallel, rather than sequentially. This minimizes latency, prevents congestion, and ensures that AI accelerators are continuously fed with high-fidelity inputs.
• Simplified System Architecture: Multi-protocol PHYs eliminate the need for separate interface components or complex switching logic. This streamlines board design, reduces BOM cost, and lowers power consumption, which are all critical for compact, thermally constrained edge deployments.
• Greater Design Flexibility: Concurrent support enables tailored interconnect strategies. Designers can dedicate PCIe lanes to GPU or NPU accelerators, while Ethernet handles distributed sensor fusion and control traffic without tradeoffs or reconfiguration overhead.

By enabling true concurrency across PCIe and Ethernet, multi-protocol interconnects eliminate bottlenecks and unlock a new level of performance and efficiency. This architecture ensures synchronized, low-latency data flow from sensors to compute to acceleration—empowering autonomous systems to operate with the speed, precision, and resilience required at the edge.

See It in Action

To explore the technology behind this multi-protocol flexibility, check out our demo video:

• ️ 1:40 – 2:30: Multi-Protocol PHY in Action
  This segment shows PCIe 5.0 and 25G Ethernet links running concurrently on a single PHY, demonstrating its ability to maintain signal integrity and consistent performance across protocols. This is a foundational capability for edge AI systems, such as autonomous platforms.

This demonstration underscores the interconnect agility required for next-gen edge AI, where multi-protocol integration isn't just beneficial, it's mission-critical.

Learn more about Cadence concurrent multi-protocol solutions.