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Engineering notes, scaling guides and case studies on open networking — SONiC switching, VPP routing, optics and OpenWiFi.
From KV Cache to RoCE: Why AI Inference Needs a High-Performance Network
As model size, context length, concurrency, and AI workloads grow, the memory and compute of a single GPU reach their limit. Inference systems then…
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LLM Inference and KV Cache: Where AI Inference Cost Comes From
Two concepts are required for anyone who uses large language models (LLMs) or builds applications on them: Inference and the KV Cache (key-value cache).…
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RoCEv2 vs. InfiniBand in AI Fabrics: Architecture, Benchmark & Selection Guide
As GPU clusters scale from hundreds to tens of thousands of accelerators, the interconnect fabric — not raw compute — increasingly decides how much…
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AsterNOS SRv6 DCI Cross-Domain Interconnection: Option A/B/C Architecture & Selection Guide
In traditional enterprise and cloud-provider networks, the data center (DC) internal network (typically built on a VXLAN overlay) and the external wide-area network (WAN,…
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Asteraix 100G-1.6T AI & Cloud Data Center Switch Overview
We delivers a next-generation Ethernet switching platform designed for the evolving needs of AI, HPC, storage, and cloud infrastructure. Covering speeds from 100G to…
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How to Choose the Right 100G Switch for AI, HPC, NVMe and Cloud Workloads: A Complete Guide
In today's data center infrastructure evolution, 100G has unambiguously become the mainstream standard. Whether it's the full-scale rollout across public cloud hyperscaler networks or…
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Scale-Up, Scale-Out, and Scale-Across: The Three Core Scaling Strategies in AI Data Centers
With the rapid advancement of artificial intelligence models, model sizes are growing at an unprecedented pace. From large language models to multimodal models, the…
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400G vs 800G Switch: How to Actually Choose for Your AI Network
As AI clusters continue to grow and data center traffic patterns evolve, choosing the right network is no longer just a matter of "how…
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