65 citations · 72 across the 3 of their papers we have counts for
3 papers
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…
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…
An Electro-Photonic System for Accelerating Deep Neural Networks
Cansu Demirkiran, Furkan Eris, Gongyu Wang +7
The number of parameters in deep neural networks (DNNs) is scaling at about 5 the rate of Moore's Law. To sustain this growth, photonic computing is a promising avenue, as…