MLonMCU: TinyML Benchmarking with Fast Retargeting

• URL: http://arxiv.org/abs/2306.08951v1
• Date: Thu, 15 Jun 2023 08:44:35 GMT
• Title: MLonMCU: TinyML Benchmarking with Fast Retargeting
• Authors: Philipp van Kempen, Rafael Stahl, Daniel Mueller-Gritschneder, Ulf Schlichtmann
• Abstract summary: It is non-trivial to choose the optimal combination of frameworks and targets for a given application. 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.
• Score: 1.4319942396517
• License: http://creativecommons.org/licenses/by/4.0/
• 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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