[lamchob]

In the area of AutoTuning some machine learning methods are used. The goal is to optimize throughput or latency for compute intensive workloads. The machine learning model is trained with performance measurements on the hardware and then use it as proxy for real execution to try out different configurations.

Notable works:

AutoTVM - https://arxiv.org/abs/1805.08166

CHAMELEON - https://deepai.org/publication/chameleon-adaptive-code-optim...

GPU-Warp Scheduling - https://deepai.org/publication/rlws-a-reinforcement-learning...