CEA-Leti Scientists Present In-Memory Computing Pathways for Edge-AI & Neural Networks with 3D Architectures & Resistive-RAM
CEA-Leti Scientists Present In-Memory Computing Pathways for Edge-AI & Neural Networks with 3D Architectures & Resistive-RAM Papers at IEDM 2020 Explore Ways to Leverage 3D Technology’s Strengths For Lowering Device Energy Consumption and Energy Lost in Data Transmission GRENOBLE, France – Dec. 17, 2020 – CEA-Leti presented two papers this week at IEDM 2020 that confirm the advantages of combining 3D architectures and resistive-random-access-memories (RRAM) for in-memory computing (IMC)...
Sylvain Barraud Elisa Vianello Eduardo Esmanhotto Cell For Neural Networks Stacked Nanosheet Transistors Monolithically Integrated Multiple
Source: eejournal.com