BanditWare uses a decaying epsilon-greedy contextual bandit with linear runtime models to recommend hardware for scientific workflows, learning online with far fewer samples than offline ML approaches.
Extreme heterogeneity 2018 - productive computational science in the era of extreme heterogeneity: Report for doe ascr workshop on extreme heterogeneity,
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BanditWare: A Contextual Bandit-based Framework for Hardware Prediction
BanditWare uses a decaying epsilon-greedy contextual bandit with linear runtime models to recommend hardware for scientific workflows, learning online with far fewer samples than offline ML approaches.