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arXiv · 2307.12713

Formal description of ML models for unambiguous implementation

Adrien Gauffriau·Iryna De Albuquerque Silva·Claire Pagetti
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Abstract

Implementing deep neural networks in safety critical systems, in particular in the aeronautical domain, will require to offer adequate specification paradigms to preserve the semantics of the trained model on the final hardware platform. We propose to extend the nnef language in order to allow traceable distribution and parallelisation optimizations of a trained model. We show how such a specification can be implemented in cuda on a Xavier platform.

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Adrien Gauffriau, Iryna De Albuquerque Silva, Claire Pagetti. 2023-07-24. Formal description of ML models for unambiguous implementation. https://arxiv.org/abs/2307.12713

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