Course

Validating 1.6T AI Data Centers

Courses
15 items

Join Keysight engineers for an in-depth bootcamp for network architects building AI infrastructure at 1.6T speeds. Through real-world demos and step-by-step guides, explore innovative solutions to validate AI data centers with full-stack visibility, stress-test 1.6T Ethernet interconnect performance from Layer 1 - 3, and ensure transceiver reliability and interoperability under realistic AI traffic conditions. This content can help maximize AI network performance and minimize GPU idle time in your next upgrade.

Learn:

Emulate realistic AI workloads to test every data path in your system.
Validate high-speed Ethernet interconnect performance, stability, and multi-vendor interoperability.
Scale 1.6T transceiver manufacturing tests with advanced optical sensitivity and higher TDECQ accuracy.

This bootcamp is ideal for network architects and engineers focused on optimizing throughput, performance, and scalability for next-gen AI data centers.

Lessons

Webinars

Lesson 1 - AI Showcase: Innovations to Scale AI Data Centers

AI is pushing networks to their limits — trillion-parameter models, millions of GPUs, and nonstop upgrade cycles. For network architects, the pressure is immense: one weak link can disrupt everything. Discover three innovations that let you validate every data path and every network component at 1.6T speeds — with deep insight across all layers. Ready to upgrade with full-system confidence?

White Papers

Improving Scalability in AI Data Center Cluster

As AI models grow more complex and larger, effectively scaling data center clusters has evolved into a mission-critical priority for organizations aiming to stay competitive. This white paper explores the rise of AI clusters, highlights the key scaling challenges — particularly within network infrastructure — and demonstrates how advanced emulation solutions can help you overcome these obstacles.

White Papers

How AI Networks Differ from Traditional Networks

Artificial intelligence (AI) and machine learning (ML) are driving big changes in data center networks — including new requirements, traffic patterns, and technologies. Discover how Keysight solutions help optimize AI networks.

Lesson 2 - A Q&A with Alex Bortok on the Keysight AI Data Center Builder

Keysight’s Alex Bortok explores how AI is transforming data center design. As generative AI models surge, two major challenges have emerged. First, a global shortage of GPUs made it nearly impossible to build test labs. Second, the AI ecosystem — models, software, hardware — was changing so fast, no static solution could keep up. In this interview video, you will learn how Keysight AI (KAI) Data Center Builder emulates real-world AI workloads, enabling the design and validation of next-gen data center networks without expensive GPUs.

Solution Briefs

AI / ML Infrastructure Evaluation and Benchmarking

This solution brief introduces how Keysight AI (KAI) Data Center Builder addresses these challenges by accelerating AI / ML networks and input/output innovation cycles. This innovative software uses high-density traffic load appliances that support 100-800GE ports to emulate AI hosts and realistic AI / ML traffic patterns. You will learn how KAI Data Center Builder can help speed up releases, lower costs, simplify setup and maintenance, and improve overall performance.

White Papers

AI Infrastructure: Optimized for Model Training

This white paper discusses the critical infrastructure needed for efficient AI model training, emphasizing the role of network capabilities in handling vast data flows and minimizing delays. It outlines challenges in model training and innovative solutions that can enhance performance.

Application Notes

AI Fabric Test Methodology

In the context of Artificial Intelligence (AI) systems, particularly Large Language Models (LLMs), a network fabric refers to the underlying infrastructure that connects and enables communication between various components or nodes within the system. The network fabric is crucial in facilitating efficient and effective AI system operation, including LLM training.

Demos

Lesson 3 - Testing 800G and 1600G Ethernet Interconnects

Explore Keysight’s latest 800G and 1600G Ethernet test solutions for validating high-performance interconnects, including active cables and immersed optical transceivers in data centers.

White Papers

Future-Proofing Networks with 1.6T Ethernet

This white paper delves into the key challenges of validating interconnect performance in the context of 1.6T Ethernet. It explores the growing demands on data centers, the limitations of existing network architectures, and the emerging technologies and testing methodologies required to ensure the reliable deployment of these high-speed networks.

Solution Briefs

1600GE Interconnect and Network Performance Test

The Interconnect and Network Performance Tester 1600GE (INPT-1600GE) is a versatile high speed Ethernet platform, available in a portable, lightweight, office quiet benchtop or rackmount chassis. The platform validates performance and reliability from 200GE to 1600GE in a range of Ethernet devices and interconnects that use 212Gb/s electrical lane interfaces.

Application Notes

Validating 800GE and 1.6TE Interconnects

Resilient 800GE and 1.6T Ethernet data center interconnects play a vital role in maximizing AI network performance. While they promise greater data rates and lower latencies, these transceivers will introduce higher modulation formats, more sensitive components, and increased susceptibility to impairments. To meet demanding performance requirements and ensure future scalability, interconnect vendors must validate both compliance with evolving standards and seamless interoperability with existing data center infrastructure. This application note explores the significant opportunities emerging in the rapidly growing AI/ML data center market and addresses the key challenges vendors face, such as maintaining high signal integrity, optimizing power consumption, and ensuring compatibility with modern network architectures. It also outlines a comprehensive set of test strategies, including rigorous performance testing, interoperability assessments, and adherence to industry standards. These strategies are crucial for the successful deployment of interconnects in AI data centers.

Demos

Lesson 4 - How to Optimize Hardware Utilization for 400G / 800G / 1.6T Optical Tx with Flex

This video demonstrates optimizing test hardware utilization with FlexOTO software in different test configurations to achieve a lower cost-of-test for 400G/800G/1.6T optical transceiver validation.

White Papers

800G / 1.6T Data Center Transceiver Test

This white paper delves into AI data center trends, addressing how hyperscale data center architects and operators must scale networks from 400G to 800G / 1.6 terabit (1.6T) Ethernet to meet these demands. This guide explores key strategies to increase interconnect bandwidth, ensure interoperability and reliability, and reduce test time, power, and cost.

Application Notes

TDECQ Measurement Update

This paper discusses how the measurement of TDECQ has evolved and improved, and what users of Keysight systems should expect for accuracy and consistency for a wide variety of test scenarios.

Application Notes

Optimizing Cost of Data Center Optical Transceiver Test

Methods to improve DCA channel utilization and reduce measurement cost per transmitter test

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