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While there exist many ways to deploy machine learning models onmicrocontrollers, it is non-trivial to choose the optimal combination offrameworks and targets for a given application. Thus, automating the end-to-endbenchmarking flow is of high relevance nowadays. A tool called MLonMCU isproposed in this paper and demonstrated by benchmarking the state-of-the-artTinyML frameworks TFLite for Microcontrollers and TVM effortlessly with a largenumber of configurations in a low amount of time.

MLonMCU: TinyML Benchmarking with Fast Retargeting