Introduction:

As network fabrics scale to support next-generation AI clusters and workloads, the industry is confronting a harsh physical-layer reality. Recent laboratory benchmarks evaluating 1.6 Terabit Ethernet (1.6T) data streams confirm that under saturated, wire-speed workloads, traditional packet-forwarding logic triggers instantaneous Physical layer (PHY) memory buffer exhaustion.

Recently released laboratory validation data provides the first definitive, real-world proof that the 1.6 Terabit Ethernet (1.6T) PHY layer packet loss problem has been solved in hardware.  That’s enabled the networking industry to go from theoretical design to proven physical deployment for next-generation multi-terabit fabrics. While the Open Compute Project (OCP) outlined the architectural blueprint for Ethernet for Scale-Up Networks (ESUN) in February 2026, the live telemetry published  from production-ready merchant silicon testbeds establishes a critical milestone: under saturated, wire-speed workloads, hardware-enforced Credit-Based Flow Control (CBFC) at the Media Access Control (MAC) layer successfully prevents physical layer (PHY) memory buffer exhaustion. In synchronized, collective AI training workloads (such as All-Reduce), dropping a single packet introduces a catastrophic tail-latency penalty that leaves expensive GPU clusters sitting idle.

This solution is primarily based on the data link-layer protocol stack defined by the Open Compute Project’s (OCP’s) Ethernet for Scale-Up Networks (ESUN) specification which was successfully tested at the OCP Summit last week by Keysight.

Last week’s hardware test results confirm that by combining the physical signaling foundation of the IEEE P802.3dj Task Force (within the IEEE 802.3 Working Group) with the active pacing blocks of the OCP ESUN specification, silicon architects can guarantee zero-packet-discard performance at full 1.6T line rates without relying on physically impractical silicon buffer footprints.

The Root Cause – Synchronized Bursts vs. PHY Buffers:

Traditional Ethernet was designed for asynchronous, distributed internet traffic where transient congestion could be absorbed by deep-buffer switches or managed gracefully by top-of-stack TCP/IP windows. AI scale-up environments flip this paradigm. Thousands of processing nodes push traffic simultaneously in synchronized, bursty phases. When a 1.6T pipe—operating on 8 channels of 224G SerDes using PAM4 modulation—receives an unpaced burst, the sheer data density overflows the tight SRAM allocation of the physical coding and routing components.

+-------------------------------------------------------------------------+

|                  AI WORKLOAD LAYER (All-Reduce / Collective Communications) |
+-------------------------------------------------------------------------+

|                 OCP ESUN LINK LAYER (Base Specification 1.0)             |
|   - 4-Byte Segmented Frame Header (Stripped of traditional IP overhead) |
|   - Credit-Based Flow Control (Proactive virtual-channel buffering)     |
|   - Link-Level Retry (Microsecond-range local hardware error recovery)  |
+-------------------------------------------------------------------------+

|                 IEEE P802.3dj PHYSICAL LAYER (Draft Amendment)          |
|   - Multi-rate MAC Configuration (1.6 Terabits per second throughput)   |
|   - Concatenated Forward Error Correction (Inner & Outer RS-FEC)        |
|   - Physical Media Dependent Signaling (8 Lanes x 224G SerDes via PAM4) |
+-------------------------------------------------------------------------+

|                 PHYSICAL LAYER MEDIA (Data Center Infrastructure)       |
|   - OS2 Single-Mode Fiber (Max 500m via DR8 / Max 2km via 2xFR4 WDM)    |
|   - MPO-16 / MTP-16 High-Density Connectors                             |
+-------------------------------------------------------------------------+

OCP ESUN – Network Operator Requirements – Base Specification 1.0.   https://www.opencompute.org/news/the-ocp-esun-10-specification-has-been-released/