NEW CASTLE, DE — FS launched an 800G Ethernet networking platform designed for NVIDIA B300 GPU clusters, positioning the company to compete in the rapidly expanding market for AI data center infrastructure as demand for high-bandwidth computing accelerates.
The company said the new platform uses a 51.2-terabit RoCEv2 Ethernet architecture intended to support large-scale artificial intelligence training workloads that require low-latency and lossless connectivity across GPU clusters.
The launch reflects growing pressure on networking vendors to address infrastructure bottlenecks emerging from increasingly powerful AI accelerators, including next-generation GPU systems from NVIDIA.
FS said traditional data center network architectures are struggling to meet the bandwidth, congestion management, and scalability demands created by large AI training models.
The system is built on an 800G Ethernet Spine-Leaf fabric architecture and incorporates the company’s PicOS network operating system alongside AmpCon data center management software.
According to the company, the platform is designed to automate deployment, centralize monitoring, and simplify management across large AI networking environments.
Key features include support for priority flow control, Data Center Quantized Congestion Notification, intelligent load balancing, and dedicated RDMA storage networking intended to reduce latency during AI model training.
The company said the architecture is designed to support horizontal scaling across large GPU deployments while maintaining network stability and throughput.
FS framed the rollout as part of a broader push into AI-focused infrastructure markets, where networking performance has become increasingly critical as enterprises and cloud providers scale generative AI and machine learning operations.
The launch also signals continued industry momentum behind Ethernet-based AI networking alternatives as hyperscalers and enterprise operators evaluate lower-cost and more flexible approaches to connecting large GPU clusters.
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