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A Scalable NorthPole System with End-to-End Vertical Integration for Low-Latency and Energy-Efficient LLM Inference

Fuente: arXiv

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Bibliographic Details
Main Authors:	DeBole, Michael V., Appuswamy, Rathinakumar, McGlohon, Neil, Taba, Brian, Esser, Steven K., Akopyan, Filipp, Arthur, John V., Amir, Arnon, Andreopoulos, Alexander, Carlson, Peter J., Cassidy, Andrew S., Datta, Pallab, Flickner, Myron D., Gandhasri, Rajamohan, Garreau, Guillaume J., Ito, Megumi, Klamo, Jennifer L., Kusnitz, Jeffrey A., McClatchey, Nathaniel J., McKinstry, Jeffrey L., Nayak, Tapan K., Otero, Carlos Ortega, Penner, Hartmut, Risk, William P., Sawada, Jun, Sivagnaname, Jay, Smith, Daniel F., Sousa, Rafael, Terrizzano, Ignacio, Ueda, Takanori, Gray-Donald, Trent, Cox, David, Modha, Dharmendra S.
Format:	Preprint
Published:	2025
Subjects:	Distributed, Parallel, and Cluster Computing Artificial Intelligence Hardware Architecture
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2511.15950