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Design of Analog-AI Hardware Accelerators for Transformer-based Language Models (Invited)

  • Published:2023-12-09 Issue: Volume:25 Page:1-4
  • ISSN:
  • Container-title:2023 International Electron Devices Meeting (IEDM)
  • language:
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Author:

Burr G. W.1,Tsai H.1,Simon W.2,Boybat I.2,Ambrogio S.1,Ho C.-E.1,Liou Z.-W.1,Rasch M.3,Büchel J.2,Narayanan P.1,Gordon T.4,Jain S.3,Levin T. M.4,Hosokawa K.5,Le Gallo M.2,Smith H.1,Ishii M.5,Kohda Y.5,Chen A.1,Mackin C.1,Fasoli A.1,ElMaghraoui K.3,Muralidhar R.3,Okazaki A.5,Chen C. -T.3,Frank M. M.3,Lammie C.2,Vasilopoulos A.2,Friz A. M.1,Luquin J.1,Teehan S.4,Ahsan I.4,Sebastian A.2,Narayanan V.3

Affiliation:

1. IBM Research-Almaden,San Jose,CA,USA

2. IBM Research-Zurich,Rüschlikon,Switzerland

3. IBM Research-T. J. Watson Research Center,Yorktown Heights,NY,USA

4. IBM Albany NanoTech,Albany,NY,USA

5. IBM Tokyo Research Laboratory,Tokyo,Japan

Publisher

IEEE

Reference23 articles.

1. Imagenet classification with deep convolutional neural networks;Krizhevsky

2. Deep Learning with Limited Numerical Precision;Gupta

3. Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks;Hoefler;J. Mach. Learn. Res.,2021
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