Overview#

The NVIDIA Enterprise RA using the 2-8-9-800 node architecture with NVIDIA HGX B300 and NVIDIA Spectrum-X Networking is optimized for workloads of multi-node AI or hybrid applications. The Enterprise RA is a modular architecture based on NVIDIA-Certified HGX B300 systems, each with eight B300 SXM GPUs. Using a four-node scalable unit (SU) – (Refer to Figure 8 below), this Enterprise RA scales up to 128 NVIDIA-Certified HGX B300 systems for a total of 1024 B300 SXM GPUs.

  • A fully tested system scales to 32 SUs (Scalable Units). Larger clusters can be built based on customer requirements.

  • Flexible rail-optimized end-of-row network architecture that can accommodate modifications in the rack layout and number of servers per rack.

Hardware support is available through the fulfillment system and channel partners. Software support from NVIDIA is based on a per GPU paid subscription of NVIDIA AI Enterprise and NVIDIA Run:ai.

The NVIDIA HGX B300 and NVIDIA Spectrum-X Networking Platform Enterprise RA enables the following use cases:

  • AI Inference—Large (per node) and Medium (per GPU) model parameter inference workload.

  • AI Training––Large to small model training and fine tuning based on cluster sizing.

  • Large-scale data analytics – GPU-accelerated big data analytics with simplified ETL processes and fewer data transfer bottlenecks.

Our Sizing Guides provide guidance on typical characteristics and models supported for various workloads.

For all use cases, this architecture is ideal for multi-user, single tenant workloads. Specifically, the logical design and software is streamlined for deployment and maintenance ease by tailoring the configuration to one where users are all part of the same enterprise, and accounting and access control can be consolidated.

Similarly, Kubernetes is the modern foundation of enterprise AI work, and this Enterprise RA is architected for deploying Kubernetes and Kubernetes-dependent applications and tooling.