37 citations · 116 across the 11 of their papers we have counts for
11 papers
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator
Abhishek Tyagi, Reiley Jeyapaul, Chuteng Zhu +2
As Neural Processing Units (NPU) or accelerators are increasingly deployed in a variety of applications including safety critical applications such as autonomous vehicle, and medic…
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator
Chuteng Zhou, Fernando Garcia Redondo, Julian Büchel +7
Always-on TinyML perception tasks in IoT applications require very high energy efficiency. Analog compute-in-memory (CiM) using non-volatile memory (NVM) promises high efficiency a…
Active multi-fidelity Bayesian online changepoint detection
Gregory W. Gundersen, Diana Cai, Chuteng Zhou +2
Online algorithms for detecting changepoints, or abrupt shifts in the behavior of a time series, are often deployed with limited resources, e.g., to edge computing settings such as…
Information contraction in noisy binary neural networks and its implications
Chuteng Zhou, Quntao Zhuang, Matthew Mattina +1
Neural networks have gained importance as the machine learning models that achieve state-of-the-art performance on large-scale image classification, object detection and natural la…
Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation
Chuteng Zhou, Prad Kadambi, Matthew Mattina +1
The success of deep learning has brought forth a wave of interest in computer hardware design to better meet the high demands of neural network inference. In particular, analog com…
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning
Paul N. Whatmough, Chuteng Zhou, Patrick Hansen +3
The computational demands of computer vision tasks based on state-of-the-art Convolutional Neural Network (CNN) image classification far exceed the energy budgets of mobile devices…
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning
Paul Whatmough, Chuteng Zhou, Patrick Hansen +1
On-device CNN inference for real-time computer vision applications can result in computational demands that far exceed the energy budgets of mobile devices. This paper proposes Fix…
Plasma electron hole oscillatory velocity instability
Chuteng Zhou, Ian H. Hutchinson
In this paper, we report a new type of instability of electron holes (EHs) interacting with passing ions. The nonlinear interaction of EHs and ions is investigated using a new theo…
Plasma electron-hole kinematics: momentum conservation
I H Hutchinson, C T Zhou
We analyse the kinematic properties of a plasma electron hole: a non-linear self-sustained localized positive electric potential perturbation, trapping electrons, that behaves as a…
Kinetic Electron and Ion Instability of the Lunar Wake Simulated at Physical Mass Ratio
Christian Bernt Haakonsen, Ian H. Hutchinson, Chuteng Zhou
The solar wind wake behind the moon is studied with 1D electrostatic particle-in-cell (PIC) simulations using a physical ion to electron mass ratio (unlike prior investigations); t…
Non-linear Plasma Wake Growth of Electron Holes
I. H. Hutchinson, C. B. Haakonsen, C. Zhou
An object's wake in a plasma with small Debye length that drifts \emph{across} the magnetic field is subject to electrostatic electron instabilities. Such situations include, for e…