NVIDIA Networking

Standard data centre networking works well for many business applications and virtualised environments. Pressure usually appears when AI, HPC, storage and large-scale data workloads begin demanding more bandwidth and faster system-to-system communication.

Nvidia Networking platforms support high-performance Ethernet, InfiniBand, adapters and DPUs designed for demanding compute environments. This helps organisations move data more efficiently, reduce network bottlenecks and scale infrastructure more cleanly as workloads grow.

Ethernet remains the right fit for most enterprise networking. The difference becomes noticeable when AI training or HPC workloads rely on extremely fast communication between servers across a cluster.

Nvidia Quantum InfiniBand switches such as the QM8700, QM8790, QM9700 and QM9790 are designed for these tightly connected environments, helping large compute jobs complete faster and more consistently.

Not every AI or HPC environment needs 400Gb/s networking immediately. Many research, engineering and mid-sized AI clusters still need very low latency and high throughput without the added cost and scale of NDR infrastructure.

The QM8700 and QM8790 provide 200Gb/s HDR InfiniBand connectivity in a compact 1U design, making them a practical fit for growing AI and HPC environments where HDR performance still matches operational demand.

Embedded switch management can work well in smaller isolated clusters. The challenge comes when larger AI or HPC environments need consistent provisioning, monitoring and operational control across the whole fabric.

Externally managed switches such as the QM8790 and QM9790 are better suited to centrally managed estates where IT teams want standardised control, monitoring and lifecycle management across multiple clusters.

InfiniBand is designed for tightly coupled AI and HPC workloads, but many organisations still need high-speed Ethernet that integrates naturally with existing enterprise infrastructure.

Spectrum Ethernet switches such as the SN2010, SN2100, SN2410 and SN2700 support storage, virtualisation, AI and application environments using familiar Ethernet operations. This makes them easier to integrate into mixed enterprise estates without introducing a separate networking model.

Larger leaf switches can provide more scale than smaller environments actually require. For edge locations, compact racks and smaller compute pods, that can increase cost, power usage and unused capacity unnecessarily.

Compact switches such as the SN2010 and SN2100 give organisations modern high-speed connectivity in a smaller footprint, helping teams support storage, AI and application workloads without overbuilding the rack.

100GbE networking remains suitable for many environments. The pressure point usually comes when AI, analytics, storage and distributed compute workloads begin generating more east-west traffic than the existing network can comfortably handle.

The SN3700 supports 200GbE environments, while the SN4700 supports 400GbE aggregation for larger fabrics. Higher-speed switching helps organisations move larger volumes of data with fewer bottlenecks as compute density increases.

Moving straight to 400GbE can increase optical costs and infrastructure complexity if most of the environment still operates at 100GbE.

The SN4600C provides high-density 100GbE aggregation in a 2U platform, making it a strong fit for organisations that need large-scale 100GbE connectivity without redesigning the wider fabric around 400GbE.

Traditional server designs rely heavily on the host CPU for networking, storage and security tasks. As environments become more virtualised, distributed or AI-driven, that overhead can begin consuming resources needed for applications and workloads.

BlueField DPUs offload infrastructure services from the host CPU, helping organisations improve workload isolation, strengthen infrastructure control and free server resources for production tasks.

Full DPU offload is valuable when infrastructure services need to be isolated from application workloads. Some AI environments, however, are focused primarily on moving data between GPU servers as efficiently as possible.

BlueField-3 SuperNIC is better suited to high-speed GPU networking environments focused on AI training and accelerated compute. BlueField-3 DPU is the stronger fit where networking, storage and security services also need to be offloaded from the server.

Standard network adapters can become a limitation once servers begin handling larger AI, storage or distributed compute workloads. Higher throughput and lower latency become increasingly important as infrastructure scales.

ConnectX adapters are designed for high-performance Ethernet and InfiniBand environments. ConnectX-6 supports mature 100/200GbE deployments, ConnectX-7 expands into 400GbE environments, and ConnectX-8 is designed for very large AI infrastructures requiring up to 800Gb/s connectivity.

A full infrastructure redesign can be disruptive and expensive when the real limitation exists in only a few areas of the environment.

Nvidia Networking platforms allow organisations to upgrade specific pressure points such as rack networking, cluster interconnects, adapters or infrastructure offload. This gives IT teams a more controlled way to scale AI, storage and high-performance environments without rebuilding the wider estate before it becomes necessary.