Reliability benefits of a metallic liner in confined PCM. - Wanki Kim; SangBum Kim; Robert L. Bruce; Fabio Carta; G. Fraczak; A. Ray; Chung Lam; Matthew BrightSky; Yu Zhu; T. Masuda; K. Suu; Yujun Xie; et al. (IRPS, 2018)

A Flexible and Fast PyTorch Toolkit for Simulating Training and Inference on Analog Crossbar Arrays. - Malte J. Rasch; Diego Moreda; Tayfun Gokmen; Manuel Le Gallo; Fabio Carta; Cindy Goldberg; Kaoutar El Maghraoui; Abu Sebastian; Vijay Narayanan (AICAS, 2021)

A Switched-Capacitor Integer Compute Unit with Decoupled Storage and Arithmetic for Cloud AI Inference in 5nm CMOS. - Ankur Agrawal; Monodeep Kar; Kyu-Hyoun Kim; Sergey V. Rylov; Jinwook Jung; Seiji Munetoh; Kohji Hosokawa; Xin Zhang 025; Bahman Hekmatshoartabari; Fabio Carta; Martin Cochet; Robert Casatuta; et al. (VLSI Technology and Circuits, 2023)

Fast offset corrected in-memory training. - Malte J. Rasch; Fabio Carta; Omobayode Fagbohungbe; Tayfun Gokmen (CoRR, 2023)

Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference. - Manuel Le Gallo; Corey Lammie; Julian Büchel; Fabio Carta; Omobayode Fagbohungbe; Charles Mackin; Hsinyu Tsai; Vijay Narayanan; Abu Sebastian; Kaoutar El Maghraoui; Malte J. Rasch (CoRR, 2023)

State-Independent Low Resistance Drift SiSbTe Phase Change Memory for Analog In-Memory Computing Applications. - H. Y. Cheng; Z. L. Liu; A. Majumdar; Alexander Grun; A. Ray; J. Su; Malte J. Rasch; Fabio Carta; Lynne M. Gignac; C. Lavoie; C. W. Cheng; M. Bright Sky; et al. (VLSI Technology and Circuits, 2024)

Backside Power Distribution for Nanosheet Technologies Beyond 2nm. - Ruilong Xie; Wonhyuk Hong; Chen Zhang; Jongjin Lee; Kevin Brew; Richard Johnson; Nicholas A. Lanzillo; Hosadurga Shobha; Taesun Kim; Panjae Park; Shogo Mochizuki; Iqbal Saraf; et al. (VLSI Technology and Circuits, 2024)