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LogiNet focuses on enhancing the efficiency of deep neural networks by examining their logic functions post-training. The project aims to reduce energy consumption and improve performance by developing new methodologies for executing these networks on hardware, making them more suitable for various applications, from e…
Deep neural networks (DNNs) have achieved great breakthroughs in many fields.
However, DNNs require massive multiply-accumulate (MAC) operations and their execution on digital hardware causes formidable energy consumption.
State-of-the-art solutions are still focusing on simply accelerating MAC operations in DNNs instead of examining their actual logic functions after training.
The blind execution of massive MAC operations in inference, however, poses critical risks to performance and energy sus…
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