PIM memory management; carbon nanotube FETs; high-degree polynomial gradients in memory; STT-MRAM; neuro-symbolic AI HW architecture; state of the semi industry; GAAFETs.
New technical papers recently added to Semiconductor Engineering’s library:
| Technical Paper | Research Organizations |
|---|---|
| PIM-MMU: A Memory Management Unit for Accelerating Data Transfers in Commercial PIM Systems | KAIST |
| Overcoming Ambient Drift and Negative-Bias Temperature Instability in Foundry Carbon Nanotube Transistors | MIT, Stanford University, Carnegie Mellon University and Analog Devices |
| 2024 State of the U.S. Semiconductor Industry | SIA |
| Computing high-degree polynomial gradients in memory | UCSB, HP Labs, Forschungszentrum Juelich GmbH, and RWTH Aachen Univ. |
| Enhancing Security and Power Efficiency of Ascon Hardware Implementation with STT-MRAM | CEA, Leti, Université Grenoble Alpes, CNRS, and Spintec |
| Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture | Georgia Tech, UC Berkeley, and IBM Research |
| Impact of Strain on Sub-3 nm Gate-all-Around CMOS Logic Circuit Performance Using a Neural Compact Modeling Approach | Hanyang University and Alsemy Inc. |
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