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You're reading from  TinyML Cookbook - Second Edition

Product typeBook
Published inNov 2023
PublisherPackt
ISBN-139781837637362
Edition2nd Edition
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Author (1)
Gian Marco Iodice
Gian Marco Iodice
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Gian Marco Iodice

Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and it's deployed on billions of devices worldwide – from servers to smartphones. Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, he's leading the ML performance optimization on Arm Mali GPUs. In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.
Read more about Gian Marco Iodice

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Running the CIFAR-10 model inference on the Arm Ethos-U55 microNPU

Now that all the necessary tools and software libraries are installed, our final step involves building the application with code generated by TVM for the Arm Ethos-U55 microNPU, on the Corstone-300 FVP.

Although it seems there is still a lot left to do, this recipe offers a solution to simplify the remaining technicalities.

In this recipe, we will show you how to modify the Ethos-U prebuilt sample available in the TVM source code to run the CIFAR-10 inference, on the Arm Ethos-U55. After making the necessary modifications, we will compile the application, using the provided Makefile and Linker scripts from the prebuilt sample, and run the compiled application on the Corstone-300 FVP.

Getting ready

The prebuilt sample considered in this recipe is available in the TVM source code within the tvm/apps/microtvm/ethosu directory (https://github.com/apache/tvm/tree/v0.11.1/apps/microtvm/ethosu...

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TinyML Cookbook - Second Edition
Published in: Nov 2023Publisher: PacktISBN-13: 9781837637362

Author (1)

author image
Gian Marco Iodice

Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and it's deployed on billions of devices worldwide – from servers to smartphones. Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, he's leading the ML performance optimization on Arm Mali GPUs. In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.
Read more about Gian Marco Iodice