AMD Strix Halo owners now have a detailed roadmap for creating high-performance RDMA clusters. The guide explains how to wire two Framework desktop mainboards with Intel E810 network cards for distributed vLLM inference using Tensor Parallelism. This addresses the growing need to run large language models across multiple GPUs when single devices hit memory limits.

The setup achieves remarkable latency improvements through Ro CE v2 protocol. Traditional TCP/IP connections suffer 70-100µs delays, while RDMA reduces this to approximately 5µs. This performance boost comes from bypassing CPU and OS kernel during data transfers between nodes. The configuration uses direct attach copper cables without requiring network switches for two-node deployments.

Cluster orchestration relies on Ray framework managing worker processes across nodes, while RCCE handles AMD's equivalent of NVIDIA's NCCL for tensor synchronization. The guide provides step-by-step instructions covering Fedora 43 host configuration, BIOS settings for iGPU memory allocation, and kernel parameter tuning for optimal RDMA performance.

Users follow the refresh_toolbox.sh script to automatically configure containers with RDMA support and custom library patches. Static IP assignment, jumbo frame MTU settings, and firewall zone configurations complete the networking setup. The result is a functioning distributed inference cluster capable of handling models exceeding single-device capacity.