Hybrid Convolutional Neural Networks with Reliability Guarantee

Hans Dermot Doran; Suzana Veljanovska

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arXiv · 2405.05146

Hybrid Convolutional Neural Networks with Reliability Guarantee

Hans Dermot Doran·Suzana Veljanovska

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Abstract

Making AI safe and dependable requires the generation of dependable models and dependable execution of those models. We propose redundant execution as a well-known technique that can be used to ensure reliable execution of the AI model. This generic technique will extend the application scope of AI-accelerators that do not feature well-documented safety or dependability properties. Typical redundancy techniques incur at least double or triple the computational expense of the original. We adopt a co-design approach, integrating reliable model execution with non-reliable execution, focusing that additional computational expense only where it is strictly necessary. We describe the design, implementation and some preliminary results of a hybrid CNN.

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Hans Dermot Doran, Suzana Veljanovska. 2024-05-08. Hybrid Convolutional Neural Networks with Reliability Guarantee. https://arxiv.org/abs/2405.05146

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