OPTIMIZING NEURAL NETWORK STRUCTURES FOR EMBEDDED SYSTEMS
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United States of America
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Issued Date -
Dec 19, 2024
app pub date -
Aug 30, 2024
filing date -
Aug 30, 2024
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Abstract
A model training and implementation pipeline trains models for individual embedded systems. The pipeline iterates through multiple models and estimates the performance of the models. During a model generation stage, the pipeline translates the description of the model together with the model parameters into an intermediate representation in a language that is compatible with a virtual machine. The intermediate representation is agnostic or independent to the configuration of the target platform. During a model performance estimation stage, the pipeline evaluates the performance of the models without training the models. Based on the analysis of the performance of the untrained models, a subset of models is selected. The selected models are then trained and the performance of the trained models are analyzed. Based on the analysis of the performance of the trained models, a single model is selected for deployment to the target platform.

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- 15 United States
- 10 France
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Patent Owner(s)
Patent Owner | Address | |
---|---|---|
TESLA INC | AUSTIN TX |
International Classification(s)
Inventor(s)
Inventor Name | Address | # of filed Patents | Total Citations |
---|---|---|---|
Iandola, Forrest Nelson | San Jose, US | 17 | 220 |
Jain, Paras Jagdish | Cupertino, US | 12 | 204 |
Sidhu, Harsimran Singh | Fremont, US | 15 | 213 |
Tomasello, Daniel Paden | Los Altos Hills, US | 5 | 97 |
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