Trial
Why?
- Large-scale model training and parallel simulations require low-latency, high-bandwidth interconnects between GPUs.
- RDMA/InfiniBand and technologies like RoCEv2 reduce communication overhead and improve scaling efficiency.
- Emerging post-RoCEv2 protocols and fabrics (e.g., UltraEthernet, RoCE extensions, and proprietary RDMA-like stacks) are gaining traction for improved determinism, telemetry, and Ethernet-native deployment models.
What?
- Standardize on supported network fabrics for distributed training clusters.
- Track and evaluate post-RoCEv2 protocols and fabrics (e.g., UltraEthernet): benchmark performance, interoperability, and vendor ecosystem maturity.
- Validate RDMA capabilities, NUMA/topology effects, and software stack readiness.
- Explore DPU/SmartNIC offloads for network & security functions in AI clusters.