Ai2 boosts GPU scheduling for high-impact AI research
ai2 revamps gpu scheduling to prioritize high-impact research, improving resource allocation for 150 internal researchers. ai2 manages thousands of nvidia h100, b200, and b300 gpus for large-scale distributed training of ai models.
ai2's ai infrastructure team, responsible for providing gpu compute capacity, targeted large, distributed training workloads. they managed thousands of nvidia h100, b200, and b300 gpus arranged in clusters ranging from 88 to 1024 gpus. the team served 150 internal researchers working on ai projects, including llm and vlm training, robotics reinforcement learning, and post-training for scientific agentic use cases. ai2 had demand for gpu time that far exceeded supply, with 2-3x more gpu requests than available. the new scheduling system aims to prioritize high-impact research while maintaining full occupancy.