A vendor offers 15 percent off if you take their Ethernet fabric instead of InfiniBand. Decide.

Both run at the same port speed, so the discount is not buying slower hardware. It is buying a different operational model and a different failure mode, and whether that is worth 15 percent depends on what your team already runs and what the fabric has to carry.

Updated Sep 2026 · Grounded in real AI infrastructure interview loops and written to a senior-engineer editorial bar, with every number worked and every diagram hand-built.

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The concepts behind this question

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Foundational

🖧 Hardware & Cluster Build-Out

Scale-Out Fabric Choice: InfiniBand XDR vs Spectrum-XOutside the NVLink domain every GPU talks over a scale-out fabric, and as of September 2026 NVIDIA sells two at the same 800 Gb/s per port: Quantum-X800 InfiniBand and Spectrum-X Ethernet. They differ in congestion handling, operational familiarity and what happens when something misbehaves rather than in headline speed. The switch radix decides how many endpoints a two-tier fabric reaches, and that single number drives the switch count, the cable count and a large part of the budget.

Core

🔌 Networking & StorageSign in

RDMA, InfiniBand and RoCEv2Training across nodes moves hundreds of gigabytes per step, and a CPU-driven TCP stack cannot feed a 400 Gb/s link. RDMA lets a NIC write straight into a remote GPU's memory with no kernel and no copies, and it runs over two fabrics: InfiniBand, which is lossless by design, and RoCEv2, which is Ethernet made lossless by configuration. The choice is operational as much as technical, and the numbers that decide it are per-GPU bandwidth, the collective's volume, and who will debug a pause storm at 3 a.m.

Foundational

🖧 Hardware & Cluster Build-Out

Colocation, Power Contracts and Site SelectionFor most organizations the constraint on deploying GPUs is not the GPUs. It is finding a hall that can deliver 100 kilowatts or more per rack, reject that heat with liquid, and sign a contract for the power years before the hardware exists. Colocation contracts price reserved capacity rather than consumption, cooling capability is what eliminates most sites, and the lead time on new electrical supply is measured in years while GPUs arrive in months.

Foundational

🖧 Hardware & Cluster Build-Out

The Bill of Materials for a Training ClusterA GPU cluster is not a pile of GPUs. A 512-GPU scalable unit built to NVIDIA's DGX SuperPOD B300 reference architecture needs 64 nodes, four separate networks, thousands of transceivers, storage that can absorb a checkpoint burst, a management plane, racks, power distribution and cooling equipment. Writing the list out in order is how a design becomes a purchase order, and the items people forget are the ones that hold up a deployment for weeks.

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Next in this trackTwo thousand GPUs are being replaced. What do you do with the old ones?Next in this trackAn entire rack stops responding at 2 a.m. Walk me through the first thirty minutes.Closest to this topicA vendor claims their accelerator beats an H100 at half the price. How do you evaluate that?

FEDITOR'S NOTE

Scored on the fabric choice being operational rather than about speed, on quantifying what a congestion problem costs, and on the team's existing skills as a real input.

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