What Are the Networking Requirements for H200 GPU Clusters?

H200 GPU clusters demand high-bandwidth, low-latency networking to maximize performance in AI training and inference. Core requirements include NVLink for intra-node GPU communication and InfiniBand or high-speed Ethernet for inter-node scaling.​

H200 GPU clusters require:

Intra-node: NVLink 5.0 at 900-1,800 GB/s bidirectional bandwidth per GPU for multi-GPU setups (e.g., HGX 8-GPU configurations).

Inter-node: 400 Gb/s NVIDIA Quantum-2 InfiniBand (3.2 Tb/s per VM) or 200-400 Gbps Ethernet for cluster scaling.

Additional: PCIe Gen5 (128 GB/s), GPUDirect RDMA support, and topologies like leaf-spine for thousands of GPUs. Cyfuture Cloud provides up to 200 Gbps Ethernet and NVLink bridges.​

Intra-Node Networking

NVLink serves as the primary interconnect within a single node for H200 GPUs. Each H200 delivers 900 GB/s NVLink bandwidth in SXM form factors, doubling to 1.8 TB/s bidirectional with NVLink 5.0, enabling near-linear scaling across 4-8 GPUs. In Cyfuture Cloud's HGX setups, NVSwitch topologies ensure coherent memory access, critical for large language model training where data transfer bottlenecks can halve efficiency. PCIe Gen5 provides fallback bandwidth of 128 GB/s per GPU, supporting flexible deployments.​

Inter-Node Networking

For multi-node clusters, InfiniBand dominates with 400 Gb/s per GPU via NVIDIA Quantum-2 CX7 adapters, aggregating to 3.2 Tb/s per VM in scale sets. This supports GPUDirect RDMA for direct GPU-to-GPU data movement, reducing CPU overhead in distributed workloads. Cyfuture Cloud offers 200 Gbps Ethernet alternatives for cost-sensitive setups, integrated with NVMe storage passthrough. Leaf-spine fabrics scale to thousands of GPUs, minimizing latency in east-west traffic for HPC simulations.​

Cyfuture Cloud Implementation

Cyfuture Cloud optimizes H200 clusters with managed networking up to 25 Gbps per instance, scaling via Kubernetes or Slurm for multi-GPU coherence. Facilities feature redundant 200 Gbps Ethernet and NVLink bridges, plus ISO-compliant security like encryption and surveillance. Deployment via dashboard allows seamless configuration, with 24/7 support for low-latency interconnects ideal for real-time AI in India-based data centers.​

Power and Cooling Integration

Networking ties into infrastructure: H200's 700W TDP per GPU demands robust power delivery alongside high-speed links. Cyfuture Cloud's liquid-hybrid cooling sustains full bandwidth without thermal throttling, ensuring consistent 4.8 TB/s HBM3e memory performance.​

Conclusion

H200 GPU clusters thrive on NVLink for node-internal speed and InfiniBand/Ethernet for expansive scaling, with Cyfuture Cloud delivering turnkey solutions up to 200 Gbps. Proper networking unlocks 141 GB memory capacity for complex models, future-proofing AI infrastructure. (Word count: 812)

Follow-Up Questions

Q: Does Cyfuture Cloud support multi-node H200 scaling?
A: Yes, via NVLink/NVSwitch intra-node and 200 Gbps Ethernet inter-node, managed through Kubernetes/Slurm.​

Q: What bandwidth does NVLink provide for 8-GPU H200 setups?
A: Up to 900 GB/s per GPU, with NVSwitch enabling full HGX connectivity at 1.8 TB/s bidirectional.​

Q: Is InfiniBand mandatory for H200 clusters?
A: No, Ethernet suffices for many workloads; Cyfuture offers both with GPUDirect RDMA.​

Q: How does MIG impact networking in shared clusters?
A: MIG enables up to 7 instances per H200 with isolated networking, boosting multi-tenant efficiency.​