192 citations · 730 across the 29 of their papers we have counts for
3 papers · 1 filter
Thales: Formulating and Estimating Architectural Vulnerability Factors for DNN Accelerators
Abhishek Tyagi, Yiming Gan, Shaoshan Liu +3
As Deep Neural Networks (DNNs) are increasingly deployed in safety critical and privacy sensitive applications such as autonomous driving and biometric authentication, it is critic…
Restructurable Activation Networks
Kartikeya Bhardwaj, James Ward, Caleb Tung +6
Is it possible to restructure the non-linear activation functions in a deep network to create hardware-efficient models? To address this question, we propose a new paradigm called…
UDC: Unified DNAS for Compressible TinyML Models
Igor Fedorov, Ramon Matas, Hokchhay Tann +3
Deploying TinyML models on low-cost IoT hardware is very challenging, due to limited device memory capacity. Neural processing unit (NPU) hardware address the memory challenge by u…