Ethernet Switches for AI and HPC

SONiCopen networkingdata centerAI fabricEthernetautomation

In brief

A buyer-focused engineering checklist for Ethernet switches in AI and HPC environments, covering fabric scale, RoCE, telemetry, optics, SONiC, and support.

Key takeaways

A buyer-focused engineering checklist for Ethernet switches in AI and HPC environments, covering fabric scale, RoCE, telemetry, optics, SONiC, and support.

Engineering Position

Ethernet is credible for AI and HPC because the industry has moved from ordinary data centre switching to AI-oriented Ethernet fabrics: high-radix switches, 400G/800G ports, RoCE traffic classes, congestion control, telemetry, and open NOS options such as SONiC. The buying risk is assuming every high-speed Ethernet switch can do that job.

Australian buyers should evaluate Ethernet switches for AI and HPC through evidence: workload scale, ASIC capability, buffer design, optics, telemetry, automation, and local support.

What Makes an AI/HPC Ethernet Switch Different

Requirement	Ordinary data centre switch	AI/HPC Ethernet switch
Traffic pattern	Mixed enterprise and server traffic.	Dense east-west, incast, all-reduce, storage bursts.
Loss tolerance	Packet loss may be recovered by TCP or applications.	Drops can stall RDMA or reduce GPU utilisation.
Queueing	Basic QoS often sufficient.	PFC, ECN, DCBX, buffer visibility, and traffic-class isolation matter.
Telemetry	Interface counters and logs.	Queue, path, congestion, drops, and flow correlation required.
Optics	Standard compatibility check.	FEC, DOM/DDM, breakout, thermal and cable plan must be tested.
Operations	CLI and SNMP may be enough.	Automation, rollback, telemetry collectors, and incident runbooks required.

Buyer Checklist

1. Fabric scale. Count GPUs, NICs, storage endpoints, management ports, and future expansion. Convert this into leaf count, spine count, oversubscription ratio, and cabling plan.

2. Port speed. Decide whether the first production design needs 100G, 200G, 400G, or 800G at each layer. IEEE P802.3dj work on 200G, 400G, 800G, and 1.6T Ethernet shows the direction of travel, but procurement should still be based on available optics, switch validation, and facility readiness.

3. RoCE readiness. Require evidence for PFC, ECN, DCBX, queue counters, PFC watchdog, and congestion recovery. A RoCE checkbox without counters and failure tests is not enough.

4. Telemetry. Ask how the switch exposes queue depth, drops, ECN marks, PFC events, path changes, and flow data. UEC, OCP ESUN, and NVIDIA Spectrum-X all emphasise that AI Ethernet depends on telemetry and congestion behaviour, not only bandwidth.

5. Optics and cabling. Validate QSFP28, QSFP-DD, OSFP, DAC, AOC, breakout, FEC mode, power, and thermal assumptions. In high-speed AI fabrics, optics are a system component, not an accessory.

6. NOS and support. SONiC can reduce NOS lock-in and align with Linux-style operations, but buyers must confirm the exact switch/NOS/ASIC/platform combination is supported.

What to Ask Vendors

Which ASIC is used, and which features are supported in the selected NOS image?
Which SONiC or enterprise SONiC release is validated?
Which optics and cable assemblies are qualified?
What are the queue, buffer, PFC, ECN, and drop counter names?
Can we run a workload-like POC with packet captures and telemetry export?
Who owns defects across hardware, NOS, ASIC SDK, SAI, optics, and automation?
What is the Australian RMA and escalation process?

Ethernet vs Proprietary Interconnects

Ethernet’s strength is ecosystem breadth: switch vendors, NICs, optics, NOS options, monitoring tools, and existing engineering skills. Proprietary interconnects may still be appropriate for very large training systems with specialised staff and tightly integrated stacks. For many enterprise private AI deployments, Ethernet can be the more operationally realistic option if the fabric is validated properly.

The Ultra Ethernet Consortium and OCP ESUN are important because they show industry-level effort to optimise Ethernet for AI and HPC at scale. That does not eliminate the need for buyer testing. It gives buyers a standards and ecosystem path to evaluate.

xSONiC Fit

xSONiC’s data center AI switches should be evaluated as part of a complete AI fabric design: AI fabric, GPU backend fabric, RoCE v2, INT telemetry, and packet broker visibility.

The stronger buying process is to request a proof-of-concept with the intended topology, optics, queue profile, telemetry collectors, and failure scenarios. That turns AI-ready claims into evidence.

Bottom Line

Ethernet switches for AI and HPC should be selected by validation, not vocabulary. The right platform proves fabric scale, RoCE behaviour, telemetry, optics stability, automation, and support ownership before it becomes the GPU backend network.

Engineering Evidence Floor

For this topic, treat the article as buyer-ready only when the fabric claim is tied to measurable acceptance data. The baseline evidence package should include the selected switch SKU, SONiC image, ASIC/SAI version, NIC firmware, optics list, RoCE policy, telemetry counters, support owner, and rollback method. In a small pilot, capture at least 30 minutes of traffic at the intended 100G/400G/800G speed, one link failure, one switch reboot, one optics fault, and one support handoff. That evidence separates a credible AI fabric plan from a bandwidth brochure.

Evidence area	What to validate	Acceptance gate	Rework trigger
Transport	PFC, ECN, DCBX, MTU, queue mapping, and CNP counters	30 minutes load test at 100G/400G/800G	RoCE is asserted but not measured
Platform	Switch SKU, ASIC, SAI, SONiC image, and optics list	2 switch roles pass upgrade and rollback	Generic compatibility is used as proof
Failure	Link loss, switch reboot, route convergence, and workload impact	3 failure cases captured with timestamps	Steady-state throughput is the only evidence
Telemetry	Queue depth, drops, optics DOM, gNMI, and packet visibility	Operators explain a slowdown within 15 minutes	GPU and network teams use different data
Support	APAC escalation, RMA, spares, and patch lifecycle	12 months operating plan approved	Ownership splits across vendors

This section deliberately avoids treating the topic as a feature checklist. The buyer should be able to hand the evidence to engineering, security, finance, and support teams and have each group understand what was tested, what failed, what was accepted, and what still needs rework. That is also the content pattern most useful for generative search: the page states a clear conclusion, names measurable parameters, identifies risk, and cites the operational proof required before deployment.

For AI and HPC buyers, the practical distinction is between a switch that can forward packets and a fabric that can keep expensive accelerators productive during congestion, maintenance, and partial failure. Procurement should therefore ask vendors to show the relationship between port speed, queue behaviour, optics health, RoCE configuration, telemetry export, and support workflow in one test record. That turns the switch discussion from headline capacity into operational evidence.

Engineering FAQ

Is Ethernet good enough for AI and HPC clusters? It can be, but only when the fabric is validated as a system. The switch ASIC, RoCE profile, PFC and ECN behaviour, optics, NIC firmware, telemetry export, and failure recovery all need to be tested together before production.

What is the most common procurement mistake? Treating port speed as the whole requirement. A 400G or 800G switch that lacks the right queue visibility, congestion counters, optics validation, or support ownership can still be a poor AI fabric choice.

Should buyers standardise on one switch vendor? Standardisation can simplify support, but SONiC and SAI make mixed hardware strategies possible when the team has the process to validate each switch, ASIC, optics, and NOS release combination.

What evidence should be requested before purchase? Ask for a lab test plan, supported optics list, SONiC image version, RoCE and telemetry examples, known caveats, upgrade procedure, and a named escalation path for ASIC, NOS, optics, and hardware faults.

Sources Reviewed

Product fit

Where xSONiC fits

xSONiC can help validate the switch, optics, software image, telemetry, and support assumptions against the actual deployment before a production order is released.