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Methods for data multiplexing in neural networks

Methods for data multiplexing in neural networks Princeton Docket # 22-3898-1 Current neural network architectures, particularly Transformers, face significant challenges due to their GPU-memory intensity, which limits throughput and increases time and energy costs during training and deployment. To address this issue, Princeton University researchers...

Published: 10/21/2024 | Inventor(s): Karthik Narasimhan, Vishvak Murahari, Carlos Jimenez, Runzhe Yang, Kai Li, Ameet Deshpande, Yushan Su

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Category(s): Computer Science and Information Technology