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Technical Paper Round-up: May 31

TinyML; Rowhammer; NBTI; Quantum computing; CMOS interface circuits; Neural sampling machine; ReRAM; Neuromorphic HW; Virtual sensors reliability

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New technical papers added to Semiconductor Engineering’s library this week.

Technical Paper Research Organizations
CFU Playground: Full-Stack Open-Source Framework for TinyML Acceleration On FPGAs Google, Purdue University and Harvard University
PROTRR: Principled yet Optimal In-DRAM Target Row Refresh ETH Zurich
Bias Temperature Instability of MOSFETs: Physical Processes, Models, and Prediction Liverpool John Moores University
Qubit teleportation between non-neighbouring nodes in a quantum network QuTech and Kavli Institute of Nanoscience, Delft University of Technology
CMOS Interface Circuits for High-Voltage Automotive Signals University of Parma and Silis s.r.l.

Neural sampling machine with stochastic synapse allows brain-like learning and inference University of Notre Dame and Department of Cognitive Sciences, University of California Irvine
Empirical Characterization of ReRAM Devices Using Memory Maps and a Dynamic Route Map Balearic Islands University, UC Berkeley, Health Institute of the Balearic Islands, International Hellenic University, Technische Universität Dresden, Universidad de Valladolid, and Aristotle University of Thessaloniki
Simulating the electronic structure of spin defects on quantum computers Argonne National Lab & University of Chicago
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware Graz University of Technology (Austria) and Intel Labs
Ensuring the Reliability of Virtual Sensors Based on Artificial Intelligence within Vehicle Dynamics Control Systems University of Duisburg-Essen, Germany

Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit for our global audience. At a minimum, papers need to be well researched and documented, relevant to the semiconductor ecosystem, and free of marketing bias. There is no cost involved for us posting links to papers.



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