GPU & HPC Colocation | AI & GPU Infrastructure

AI & GPU Infrastructure

GPU & HPC COLOCATION

Requirements, pricing, and planning for GPU cluster colocation at megawatt scale.

5 articles · Part of AI & GPU Infrastructure

Articles

Comprehensive guides and insights about gpu & hpc colocation.

IDACORE East's 1MW minimum and 120kW/cabinet liquid-cooled design for Eastern Oregon GPU clusters, pre-leasing now via LOI for Q4 2026.

How to size GPU colocation at IDACORE East's 120kW cabinets before signing an LOI — power math, cooling design, and 1MW minimum planning.

Liquid-cooled GPU colocation costs 40–60% less than cloud for long-running AI training. Here's the infrastructure math that makes it obvious.

H100 clusters demand 60–80kW per cabinet minimum. Most colo facilities cap at 10–15kW. Here's what 120kW/cabinet liquid cooling actually solves.

GPU colocation at $250/kW beats cloud GPUs for sustained AI training. Compare real costs, latency, and control for HPC workloads in 2026.

Data center power architecture, 2N redundancy, liquid cooling, and kW/cabinet planning for high-density workloads.

Cost comparisons, cloud repatriation analysis, and decision frameworks for AI workloads outgrowing hyperscalers.

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