AI/HPC Networking Technology

Traditionally, InfiniBand has been the technology of choice for AI fabric as it provides excellent performance for these kinds of applications.

InfiniBand drawbacks:

• Practically, a vendor-locked solution (controlled by Nvidia)
• Relatively expensive
• Requires a specific skillset and several fine-tuning efforts for each type of workload running on the cluster

Chassis or Clos AI fabric? What about both?
Distributed Disaggregated Chassis (DDC-AI) is the most proven architecture for building Ethernet-based open and congestion-free fabric for high-scale AI clusters.

Fabric-Scheduled Ethernet offers:

• Standard Ethernet
• AI scheduled fabric – predictable lossless cluster back-end network
• Proven performance at par with InfiniBand
• Highest AI scale (up to 32K GPUs at 800Gbps)
• Up to 30%JCT improvement compared to standard Ethernet Clos
• Over $50M total cost of ownership (TCO) reduction for an 8K-GPU cluster
• No vendor lock – supports any GPU, any NIC

Ultra Ethernet, however, relies on algorithms running on the edges of the fabric, specifically on the smart network interface cards / controllers (SmartNICs) that reside in the GPU servers.

This means:

• A heavier compute burden on those SmartNICs, higher costs
• Greater power consumption

For instance, take a move from the ConnectX-7 NIC (a more basic NIC, even though it is considered a SmartNIC) to the BlueField-3 SmartNIC (also called a data processing unit or DPU); this translates into a ~50% higher cost (per end device) and a threefold growth in power consumption.

This is also the case with another alternative to InfiniBand coming from Nvidia, the Spectrum-X solution (based on their Spectrum-4 and future Spectrum-6 ASICs).

• Another Ethernet-based solution (like that of the UEC) that resolves congestion at the end devices
• Also locked to Nvidia as a vendor