65 citations · 72 across the 3 of their papers we have counts for
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cs.LG2023★ 1 cited
INT-FP-QSim: Mixed Precision and Formats For Large Language Models and Vision Transformers
Lakshmi Nair, Mikhail Bernadskiy, Arulselvan Madhavan +3
The recent rise of large language models (LLMs) has resulted in increased efforts towards running LLMs at reduced precision. Running LLMs at lower precision supports resource const…
cs.LG2022★ 6 cited
Adaptive Block Floating-Point for Analog Deep Learning Hardware
Ayon Basumallik, Darius Bunandar, Nicholas Dronen +6
Analog mixed-signal (AMS) devices promise faster, more energy-efficient deep neural network (DNN) inference than their digital counterparts. However, recent studies show that DNNs…