Optimization Metrics for the Evaluation of Batch Schedulers in HPC
Robin Boëzennec,
Fanny Dufossé,
Guillaume Pallez
Abstract:Machine Learning techniques are taking a prominent position in the design of system softwares. In HPC, many work are proposing to use such techniques (specifically Reinforcement Learning) to improve the performance of batch schedulers. Their main limitation is the lack of transparency of their decision. This underlines the importance of choosing correctly the optimization criteria when evaluating these solutions. In this work, we discuss bias and limitations of the most frequent optimization metrics in the lit… Show more
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