356 citations · 369 across the 8 of their papers we have counts for
8 papers
Innovating at Speed and at Scale: A Next Generation Infrastructure for Accelerating Semiconductor Technologies
Richard A. Gottscho, Edlyn V. Levine, Tsu-Jae King Liu +7
Semiconductor innovation drives improvements to technologies that are critical to modern society. The country that successfully accelerates semiconductor innovation is positioned t…
Improving the Energy Efficiency and Robustness of tinyML Computer Vision using Log-Gradient Input Images
Qianyun Lu, Boris Murmann
This paper studies the merits of applying log-gradient input images to convolutional neural networks (CNNs) for tinyML computer vision (CV). We show that log gradients enable: (i)…
Low-Rank Training of Deep Neural Networks for Emerging Memory Technology
Albert Gural, Phillip Nadeau, Mehul Tikekar +1
The recent success of neural networks for solving difficult decision tasks has incentivized incorporating smart decision making "at the edge." However, this work has traditionally…
Going Beyond the Debye Length: Overcoming Charge Screening Limitations in Next-Generation Bioelectronic Sensors
Vladimir Kesler, Boris Murmann, H. Tom Soh
Electronic biosensors are a natural fit for field-deployable diagnostic devices, because they can be miniaturized, mass produced, and integrated with circuitry. Unfortunately, prog…
Separating the Effects of Batch Normalization on CNN Training Speed and Stability Using Classical Adaptive Filter Theory
Elaina Chai, Mert Pilanci, Boris Murmann
Batch Normalization (BatchNorm) is commonly used in Convolutional Neural Networks (CNNs) to improve training speed and stability. However, there is still limited consensus on why t…
BinarEye: An Always-On Energy-Accuracy-Scalable Binary CNN Processor With All Memory On Chip in 28nm CMOS
Bert Moons, Daniel Bankman, Lita Yang +2
This paper introduces BinarEye: a digital processor for always-on Binary Convolutional Neural Networks. The chip maximizes data reuse through a Neuron Array exploiting local weight…