Creating End-to-End TinyML Applications for Ethos-U NPU in the Cloud

Creating End-to-End TinyML Applications for Ethos-U NPU in the Cloud

EDGE AI FOUNDATION via YouTube Direct link

We provide a number of example applications!

7 of 7

7 of 7

We provide a number of example applications!

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Creating End-to-End TinyML Applications for Ethos-U NPU in the Cloud

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  1. 1 Intro
  2. 2 Creating TinyML applications is difficult
  3. 3 Main software stack to run ML on Cortex-M today Cortex-Mis robust and flexible, Ethos-U is dedicated ML accelerator
  4. 4 Key steps to run an inference on Cortex-M Pre-processing and post-processing is specific to a model
  5. 5 Hardware supported vs non-supported operator in the NN Example of the benefit of using hardware supported operators on Ethos-U
  6. 6 Leverage the Weight Compression of the Arm Ethos-U NPU Pruning & clustering improves performance on memory-bound models
  7. 7 We provide a number of example applications!

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