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arXiv · 2306.08951

MLonMCU: TinyML Benchmarking with Fast Retargeting

Philipp van Kempen·Rafael Stahl·Daniel Mueller-Gritschneder·Ulf Schlichtmann
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Abstract

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

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Philipp van Kempen, Rafael Stahl, Daniel Mueller-Gritschneder, Ulf Schlichtmann. 2023-06-15. MLonMCU: TinyML Benchmarking with Fast Retargeting. https://doi.org/10.1145/3615338.3618128

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