Weaknesses: OpenTuner * OpenTuner (http://opentuner.org) is a general-purpose auto-tuning framework that is widely used in compiler / automatic program optimization. The authors do not mention or compare against them. OpenTuner is built for tuning various knobs in a compiler / automatic program optimization setting. The authors only use simulated annealing. I would like to see how the optimization times compare with OpenTuner which can adaptively use different search techniques. Evaluation on larger NNs * Results from optimizing ResNet-50 would be more compelling.

Multitask learning and transfer learning have proven to be useful in the field of machine learning when additional knowledge is available to help a prediction task. We aim at deriving methods following these paradigms for use in autotuning, where the goal is to find the optimal performance parameters of an application treated as a black-box function. We show comparative results with state-of-the-art autotuning techniques. For instance, we observe an average $1.5x$ improvement of the application runtime compared to the OpenTuner and HpBandSter autotuners. We explain how our approaches can be more suitable than some state-of-the-art autotuners for the tuning of any application in general and of expensive exascale applications in particular.