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Technische Leitfäden und Infrastruktur-Einblicke
Technische Leitfäden und Fachartikel zu GPU-Servern, KI-Clustern, Rechenzentrumstechnik und Infrastrukturstrategie — geschrieben für IT-Verantwortliche und Einkaufsleiter.
Choosing the Right GPU for AI Training in 2026
H100, H200, B200 or B300? A practical decision framework based on model size, budget, and lead time — not marketing slides.
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NVIDIA B200 vs B300: What Actually Changed
Memory capacity, bandwidth, power envelope, and the workloads where the Ultra generation genuinely pays for itself.
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Building an On-Premises AI Cluster: A Complete Guide
From workload assessment to acceptance testing — the full sequence, with the decisions that are expensive to get wrong.
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Liquid Cooling for GPU Servers: When It Becomes Mandatory
Air cooling runs out somewhere around 40 kW per rack. Here is how to plan the transition to direct-to-chip.
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InfiniBand vs Ethernet for AI Training: A Deep Dive
Latency, congestion control, and cost per port — where Spectrum-X closes the gap and where it does not.
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Sizing an AI Cluster for LLM Training
Parameter count, token budget, and utilisation assumptions translated into a concrete node count.
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Data Center Power Density for GPU Racks
Planning 40 kW, 80 kW and 130 kW racks: busway, PDU, and redundancy topology implications.
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Sovereign AI and Data Residency in the Middle East
What UAE PDPL and GCC regulations actually require from AI infrastructure, in practical architectural terms.
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GPU Server Procurement in the UAE: A Buyer’s Guide
Import duties, export control, lead times, and the contract clauses that protect you when schedules slip.
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