NVIDIA NCP-AIN case studies
NVIDIA NCP-AIN · Put your knowledge to work in context.
The NVIDIA Certified Professional – AI Networking (NCP-AIN) is a professional credential aimed at engineers who design, build, and operate the accelerated network fabric underneath AI and HPC workloads. It suits data center network architects, infrastructure and platform engineers, solutions architects, and operations staff who work alongside GPU compute clusters and need to reason about how interconnect choices affect training and inference performance. The NVIDIA NCP-AIN case studies are 5 cases and about 3,155 words.
1Rail-Optimized NDR Fabric Degrades After Node Expansion
A 128-node training cluster (8 GPUs per node, 1,024 GPUs total) runs a 70B-parameter model over an NDR 400 Gb/s InfiniBand fabric in a rail-optimized layout: GPU k on every node connects to leaf k, with eight leaves per spine plane and two spine planes. After 32 new nodes were added using the same reference design, all-reduce step time rose from 41 ms to 49 ms.
712 words, about 4 min2Twelve HGX Nodes Into an Air-Cooled Colocation Hall
A colocation hall has 24 racks designed for 8 kW each, with in-row coolers rated at 12 kW per rack and room CRAC capacity of 350 kW total. Current IT load is 180 kW at a PUE of 1.55, with 22 C supply air.
709 words, about 4 min3Latency-Critical LLM Inference With an Idle GPU and a Saturated CPU
An LLM inference service runs on four A100 80 GB GPUs behind a Triton Inference Server. It serves three model variants, with a p99 latency SLO of 300 ms and a current throughput of 40 requests per second.
530 words, about 3 min4Bursting a Three-Week Training Campaign to Cloud GPUs
A research group has 48 on-premises A100 GPUs and a 300 TB training dataset on an NFS filer. It needs 200 GPUs for a three-week campaign and plans to burst to a cloud region connected by a 10 Gb/s dedicated interconnect.
671 words, about 3 min5RoCEv2 Incast Slowdown on a Spectrum-X Ethernet AI Fabric
A 64-node GPU cluster uses a 400 Gb/s Ethernet AI fabric with Spectrum-X switches, BlueField-3 DPUs, and RoCEv2. Each node has eight GPUs, and the fabric uses a lossless priority for storage and training traffic.
533 words, about 3 min