Wafer-scale AI accelerators vs. single chip GPUs; machine intelligence on wireless edge networks; topological flat-band-driven metallic thermoelectricity; all-in-one analog AI HW; centralized HPC platforms in SDVs; image classification of defects in IC manufacturing; reaction mechanisms in a chemically amplified EUV photoresist; statistics of EUV exposed nanopatterns.
New technical papers recently added to Semiconductor Engineering’s library:
Name of Paper | Research Organization |
---|---|
Performance, efficiency, and cost analysis of wafer-scale AI accelerators vs. single-chip GPUs | UC Riverside |
Machine Intelligence on Wireless Edge Networks | MIT and Duke University |
Topological Flat-Band-Driven Metallic Thermoelectricity | TU Wien, Los Alamos National Lab, Flatiron Institute et al |
All-in-One Analog AI Hardware: On-Chip Training and Inference with Conductive-Metal-Oxide/HfOx ReRAM Devices | IBM Research-Europe |
Towards Mixed-Criticality Software Architectures for Centralized HPC Platforms in Software-Defined Vehicles: A Systematic Literature Review | Daimler Truck AG and Technical University of Munich |
Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing | Infineon Technologies, University of Padova and University of Bologna |
Unraveling the Reaction Mechanisms in a Chemically Amplified EUV Photoresist from a Combined Theoretical and Experimental Approach | imec and KU Leuven |
Statistics of EUV exposed nanopatterns: Photons to molecular dissolutions | Hitachi High-Tech Corporation |
Find more semiconductor research papers here.
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