Dell and Siemon: Validating Real-World AI Networks

As AI workloads continue to scale in complexity, speed, and bandwidth demand, data center infrastructure must evolve to support increasingly intensive east-west traffic patterns, synchronized GPU communication, and latency-sensitive AI operations. The rise of 800G networking and the path toward 1.6T infrastructure are pushing the limits of switching architectures, optical connectivity, cabling systems, and workload orchestration. In this environment, infrastructure validation is no longer optional, it is foundational to ensuring AI systems can operate reliably, efficiently, and at scale.

This collaborative customer story highlights how Dell Technologies, Siemon, and Keysight came together to demonstrate what a validated 800G AI fabric looks like in practice. Rather than focusing on isolated components, the collaboration centered on proving how switching, connectivity, and realistic AI workload emulation must function together as a complete system to deliver optimized AI infrastructure performance.

At the core of the architecture was an AI network built around the Dell PowerSwitch Z9864F and Enterprise SONiC distribution by Dell Technologies. The solution enabled advanced AI-aware networking capabilities including enhanced hashing, adaptive routing, dynamic load balancing, fully stateful RoCEv2 transport, and sophisticated congestion control mechanisms designed to support demanding AI workloads.

Supporting the physical infrastructure layer, Siemon delivered high-performance connectivity solutions spanning copper and fiber technologies, including high-speed cabling systems, active optical cables, transceivers, and structured cabling designed for scalable AI back-end networks. As AI fabrics increasingly depend on ultra-low latency and deterministic performance, the physical layer becomes a critical enabler of network reliability and scalability.

Keysight brought realistic traffic emulation, benchmarking, and validation capabilities to the collaboration through AI Data Center Builder and AresONE-M. By emulating AI training workloads over stateful RoCEv2 transports, modeling multi-GPU host environments, and running collective operations such as All-Reduce and All-to-All, Keysight enabled the teams to benchmark fabric performance under realistic conditions, observe congestion behavior, and optimize workload completion performance before deployment.

The result was more than a technology demonstration. Together, Dell Technologies, Siemon, and Keysight showcased how validated AI infrastructure can help organizations reduce deployment risk, optimize network performance, and build confidence in next-generation AI architectures before production rollout. In optimized rail topologies, emulated AI traffic remained stable even in congested fabric conditions, with workload completion times maintained in microseconds—demonstrating the importance of validating the entire system rather than optimizing individual components in isolation.

As enterprises continue investing in AI infrastructure at unprecedented scale, this collaboration demonstrates how measurable proof, realistic workload validation, and ecosystem collaboration are helping transform AI ambition into operational reality for the next era of AI networking.