Technical Paper Roundup: Sept 27

FP8 HW spec for AI training/inferencing; quantum sensing; DRAM chips; equivalence checking; frequency comb generators; 2D materials for HW security; RF performance for ultra-thin indium oxide transistors; comparing neural networks; FPGA random number generator; rad-hard non-volatile magnetic latch.


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

Technical Paper Research Organizations
FP8 Formats For Deep Learning Arm, Intel, and Nvidia
Dissipative Superradiant Spin Amplifier for Enhanced Quantum Sensing University of Chicago and Simon Fraser University, British Columbia
A Case for Self-Managing DRAM Chips: Improving Performance, Efficiency, Reliability, and Security via Autonomous in-DRAM Maintenance Operations ETH Zurich
Equivalence Checking of System-Level and SPICE-Level Models of Linear Circuits University of Bremen and DFKI GmbH
High-efficiency and broadband on-chip electro-optic frequency comb generators Harvard, Stanford, Caltech, and Hyperlight
Application of 2D Materials in Hardware Security for Internet-of-Things: Progress and Perspective National University of Singapore and A*STAR
Record RF Performance of Ultra-thin Indium Oxide Transistors with Buried-gate Structure *award winner* Purdue University
If You’ve Trained One You’ve Trained Them All: Inter-Architecture Similarity Increases With Robustness Los Alamos National Laboratory (LANL)
FPGA Random Number Generator Johns Hopkins University
A Radiation-Hardened Non-Volatile Magnetic Latch with High Reliability and Persistent Storage Anhui University, Hefei University of Technology, LIRMM, and Kyutech

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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