Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks

Author:

Carmichael Zachariah1,Langroudi Hamed F.1,Khazanov Char1,Lillie Jeffrey1,Gustafson John L.2,Kudithipudi Dhireesha1

Affiliation:

1. Neuromorphic AI Lab, Rochester Institute of Technology, Rochester, NY

2. National University of Singapore, Singapore

Publisher

ACM

Reference33 articles.

1. Bengio Y. 2013. Deep Learning of Representations: Looking Forward. In Statistical Language and Speech Processing Adrian-Horia Dediu Carlos Martín-Vide Ruslan Mitkov and Bianca Truthe (Eds.). Springer Berlin Heidelberg Berlin Heidelberg 1--37. 10.1007/978-3-642-39593-2_1 Bengio Y. 2013. Deep Learning of Representations: Looking Forward. In Statistical Language and Speech Processing Adrian-Horia Dediu Carlos Martín-Vide Ruslan Mitkov and Bianca Truthe (Eds.). Springer Berlin Heidelberg Berlin Heidelberg 1--37. 10.1007/978-3-642-39593-2_1

2. A matrix-multiply unit for posits in reconfigurable logic leveraging (open)CAPI

3. Serving DNNs in Real Time at Datacenter Scale with Project Brainwave

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