39 citations · 81 across the 4 of their papers we have counts for
4 papers
Modeling and Predicting Transistor Aging under Workload Dependency using Machine Learning
Paul R. Genssler, Hamza E. Barkam, Karthik Pandaram +2
The pivotal issue of reliability is one of colossal concern for circuit designers. The driving force is transistor aging, dependent on operating voltage and workload. At the design…
Brain-Inspired Hyperdimensional Computing: How Thermal-Friendly for Edge Computing?
Paul R. Genssler, Austin Vas, Hussam Amrouch
Brain-inspired hyperdimensional computing (HDC) is an emerging machine learning (ML) methods. It is based on large vectors of binary or bipolar symbols and a few simple mathematica…
HW/SW Co-design for Reliable TCAM-based In-memory Brain-inspired Hyperdimensional Computing
Simon Thomann, Paul R. Genssler, Hussam Amrouch
Brain-inspired hyperdimensional computing (HDC) is continuously gaining remarkable attention. It is a promising alternative to traditional machine-learning approaches due to its ab…
SoftWear: Software-Only In-Memory Wear-Leveling for Non-Volatile Main Memory
Christian Hakert, Kuan-Hsun Chen, Paul R. Genssler +5
Several emerging technologies for byte-addressable non-volatile memory (NVM) have been considered to replace DRAM as the main memory in computer systems during the last years. The…