9 papers
Long-Term and Short-Term Transistor Aging in Deep Neural Networks: Impact and Mitigation
Alireza Sarmadi, Virinchi Roy Surabhi, Prashanth Krishnamurthy +3
Deep neural networks (DNNs) are used in a variety of real-world applications including, for example, image classification and speech recognition. The inference accuracy of DNN impl…
First Demonstration of 28 nm Fabricated FeFET-Based Nonvolatile 6T SRAM
Albi Mema, Simon Thomann, Narendra Singh Dhakad +1
With the staggering increase of edge compute applications like Internet-of-Things (IoT) and artificial intelligence (AI), the demand for fast, energy-efficient on-chip memory is gr…
Self-Heating and Parasitic Effects in Multi-Tier CFET Design
Sufia Shahin, Mahdi Benkhelifa, Yogesh Singh Chauhan +1
In this article, we study the impact of self-heating effects (SHEs) and middle of line (MOL) and back-end of line (BEOL) induced parasitics on multi-tier CFET design, where multipl…
Carbon-Efficient 3D DNN Acceleration: Optimizing Performance and Sustainability
Aikaterini Maria Panteleaki, Konstantinos Balaskas, Georgios Zervakis +2
As Deep Neural Networks (DNNs) continue to drive advancements in artificial intelligence, the design of hardware accelerators faces growing concerns over embodied carbon footprint…
Kolmogorov-Arnold Network for Transistor Compact Modeling
Rodion Novkin, Hussam Amrouch
Neural network (NN)-based transistor compact modeling has recently emerged as a transformative solution for accelerating device modeling and SPICE circuit simulations. However, con…
Late Breaking Results: Leveraging Approximate Computing for Carbon-Aware DNN Accelerators
Aikaterini Maria Panteleaki, Konstantinos Balaskas, Georgios Zervakis +2
The rapid growth of Machine Learning (ML) has increased demand for DNN hardware accelerators, but their embodied carbon footprint poses significant environmental challenges. This p…