How Ai2 Rebuilt Cluster Scheduling with GPU Time Budgets
Impactful scheduling for GPU clusters
What happened
Ai2 replaced its original priority scheduler with GPU time budgets, hierarchical fair allocation, and time-slice contracts, turning debates over how much GPU time each research project should get from case-by-case operational decisions into a transparent budget allocation process. Its cluster manages thousands of NVIDIA H100, B200, and B300 GPUs, with scales ranging from 88 to 1,024 GPUs, and demand from roughly 150 internal researchers has long been 2-3 times the available compute.
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