AI at Full Throttle: Why 1.6TE Interconnect Validation Must Evolve

AI training is relentless, moving petabytes of data across clusters of GPUs, NICs, and switches. But, while compute scales rapidly, network validation hasn’t kept up. A single slow or unstable 1.6T Ethernet link can create hidden bottlenecks that stall GPU performance and inflate training costs.

This white paper explores why traditional validation methods, such as scripted tests and isolated component checks, fall short in AI-scale environments.

You’ll learn:

• Why bandwidth alone doesn’t solve latency and congestion at 1.6T
• The seven validation complexities engineers face when testing 1.6TE interconnects, including RoCEv2, co-packaged optics (CPO), and LPO
• How a holistic Layer 1–3 emulation approach ensures Ethernet links are ready for real AI traffic loads

With AI data center interconnect bandwidth projected to grow 6x in five years, scalable and automated test strategies are critical. Don’t wait for post-deployment failures to reveal the weak links in your stack.

Test smarter. Scale faster. Keep AI training on track.

Download the white paper to validate your AI network at full throttle.