GPU utilisation shows compute activity, not whether capacity is actually available. A GPU can report low utilisation while remaining fully allocated to one workload. This post explains why workloads queue beside idle-looking GPUs, how allocation, memory, placement, and application bottlenecks contribute, and how GPU sharing methods differ in their tradeoffs.
Capsule:
AI workloads can wait for GPUs even when monitoring shows idle compute. A GPU with low compute activity is not necessarily available capacity for another workload because allocation rules, memory requirements, hardware compatibility, isolation, and placement constraints determine…
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