Articles by tag "AI infrastructure"

1. How to Choose a Rack Server for AI Training
   Selene Gong

   0
   The shift from cloud-based AI experimentation to large-scale, on-premise deployment is accelerating. For many organizations, running AI workloads in-house is no longer just a technical choice—it is a strategic decision driven by cost, performance, and data control. However, AI training ...
2. High-Performance AI Accelerators & GPUs Architecture, Cluster Scaling & Verified Procurement Guide (2026)
   Selene Gong

   18
   Enterprise AI infrastructure has shifted from “choosing a GPU” to designing a full-scale compute system under real-world constraints. Modern decisions must balance compute performance (TFLOPs), memory bandwidth (HBM3 / HBM3e), cluster interconnect (NVLink / NVSwitch), supply chain ...
3. High-Density Enterprise HDDs for Big Data Storage & AI Scaling Guide 2026
   Selene Gong

   18
   Enterprise data infrastructure is entering a phase where storage scaling is no longer optional—it is foundational. With AI workloads generating and consuming multi-petabyte datasets, high-density enterprise HDDs remain the most cost-efficient backbone for large-scale data lakes, cold storage, ...
4. Is 100G Ethernet Enough for AI Clusters? When to Upgrade to 400G
   Selene Gong

   18
   When building or scaling AI infrastructure, organizations often start with the compute layer, heavily investing in the latest GPUs. However, a critical question usually arises during the architectural planning phase: is 100G Ethernet enough for AI clusters, or will it throttle your expensive ...
5. NVIDIA Spectrum-X vs Traditional Ethernet for AI Networking
   Selene Gong

   18
   For AI infrastructure architects and data center engineers, deploying modern GPUs is no longer the main challenge—the real constraint is whether the network can keep those GPUs fully utilized. As organizations scale from small AI pods to large-scale LLM training clusters with hundreds or ...