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Ineffective Occupancy in Heterogeneous GPU Clusters: Prediction, Contribution Analysis, and Readiness-Aware Scheduling
In heterogeneous GPU clusters, GPUs are costly and scarce, yet placing a job on a machine does not mean that the job becomes ready to run. A large amount of allocated capacity can remain occupied for long periods without producing useful computation, further aggravating the waste of compute resource
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