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End-to-End Validation for AI Data Centers
Strengthen 1.6T network reliability for AI-scale workloads from transceivers to interconnects.
New Solutions for 1.6T Chip to Cluster Validation & Emulation
Webinar: Adapting Optical Validation Workflows to 1.6T AI Networks
Explore the latest IEEE 802.3dj updates, including new TDECQ and OMA definitions, a new reference receiver, and their impact on testing and interoperability across pluggable, LPO, and CPO architectures. Learn how standards-aligned, automated validation workflows can help identify performance limits earlier and ensure reliable optical connectivity for next-generation AI networks.
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ON-DEMAND WEBINAR:
Advance AI Fabric Validation and Workload Emulation at 1600GE
Learn how to validate AI network infrastructure by emulating real AI workloads and generating high-density traffic that mirrors GPU clusters. Test fabric performance at scale, catch issues earlier, and gain visibility from physical layer metrics to RoCEv2 traffic—so you can deploy AI infrastructure with confidence.
See End-to-End Validation in Action
Why Traditional Data Center Validation Reaches Its Limit at 1.6T
At 1.6T, AI infrastructure must now be validated under realistic workload conditions that expose latency variation, congestion behavior, interconnect instability, and workload synchronization effects before deployment.
This white paper provides expert insights on the growing gap between lab validation and production behavior in AI data centers. Discover how engineers are moving beyond isolated component testing toward end-to-end validation strategies that combine workload emulation, automation, and large-scale traffic generation.
Rethinking AI-Scale Data Center Validation
As AI data centers scale to 1.6T Ethernet and tightly coupled GPU fabrics, traditional Ethernet validation methods are no longer enough to ensure reliable, high-performance operation. This white paper examines the emerging challenges of AI-scale networking — from interoperability and congestion to tail latency and workload-driven traffic behavior — and outlines why end-to-end, system-level validation is essential for deployment readiness.
1.6T Traffic Emulation and Validation
AresONE 1600GE: Built for 1.6T AI Workload Emulation
Validate 1.6T Ethernet networks and components with AI workload emulation. Assess network performance with realistic traffic generation and protocol testing to ensure network reliability before and after deployment.
Functional Interconnect Test
Functional Interconnect Test Solutions: Multiple Lane Validation Beyond Compliance
Delivers digital-layer bit error ratio (BER) and forward error correction (FEC) performance testing of high-speed optical and copper interconnects across up to 8 lanes simultaneously for reliable, automated benchmarking across the entire product life cycle.
1.6T PHY Optical Conformance Test
1.6T PHY Validation and Compliance Solutions: Verify Device Conformance at 224 Gb/s
Automate PHY and transceiver compliance to industry standards, including 224 Gb/s single-mode and multimode optics. Characterize performance to ensure reliability at the physical layer.
Optimize Data Center Performance with End-to-End Emulation
How Juniper Networks Boosted AI Network Performance
Maximize 1.6T Optical Transceiver Test Throughput.
Related Validation and Emulation Solutions
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Laying the Groundwork for What's Next
Keysight and NTT Innovative Devices are working together to help shape the future of global communications. This alliance brings together deep technical expertise and advanced tools to overcome the toughest challenges in high-speed data transmission and move closer to next-generation optical interconnects for AI, cloud, and quantum computing.
Watch the video to see how the NTT and Keysight collaboration is replacing traditional electronic data transmission with photonics to power advanced AI systems and beyond.
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