Ai2 replaces priority GPU scheduler with budget-based fair-share system
Ai2's AI Infrastructure team replaced its priority-based GPU scheduler with a system using GPU time budgets, hierarchical fair-share allocation, and time-slicing contracts. The institute manages thousands of NVIDIA H100, B200, and B300 GPUs across 88- to 1024-GPU clusters for about 150 researchers, with demand running 2-3x available capacity. The change moved GPU allocation debates into a transparent administrative budgeting process.
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