Spirent’s solution will enable the hyperscaler to balance efficiency and sustainability, while monetising its AI Ethernet infrastructure investments.

Bangalore, December 12, 2024 – Spirent Communications, a leading provider of test and assurance solutions for next-generation devices and networks, has announced that a leading AI-focused hyperscaler has selected Spirent to perform critical 800G Ethernet fabric testing and assurance, to ensure optimal performance for AI workloads. Spirent’s solution will enable the hyperscaler to balance efficiency and sustainability, while monetising its AI Ethernet infrastructure investments.

“Artificial Intelligence is transforming the industry and this hyperscaler is leader in building the next generation public cloud for enabling large scale AI workloads,” said Aniket Khosla, Spirent’s Vice President of Wireline Product Management. “At Spirent we understand the challenges that come with building sustainable AI data center networks and supporting high-performance compute use cases, and we’re excited to support leading industry players as they address the performance demands of advanced AI applications.”

Hyperscalers globally are continuing to scale rapidly to meet the dramatic demand for accelerated compute solutions critical for training and serving the most sophisticated AI models. Leveraging Spirent’s B3 800G Appliance and proven test methodologies, Spirent is enabling hyperscalers to optimise the performance of high-speed Ethernet infrastructure required to support AI-driven applications.

The B3 800G Appliance is a high-density native 800G OSFP and QSFP-DD test platform, and the first in its class to support IEEE 802.3df specifications. It provides rigorous, high-scale testing to evaluate bandwidth and resource utilisation, helping to accelerate 800G deployments and enable the networking industry to power new applications running AI/ML. With the B3 800G Appliance, hyperscalers can test and validate their infrastructure’s readiness for bandwidth-intensive AI workloads, while maintaining optimal network efficiency. 

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