AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing
- Hadjer Benmeziane
- Corey Lammie
- et al.
- 2023
- EDGE 2023
Publications
This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.
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34 results for Ramachandran Muralidhar
Filamentary Statistical Evolution from Nano-Conducting Path to Switching-Filament for Oxide-RRAM in Memory Applications
- Ernest Wu
- Takashi Ando
- et al.
- 2019
- IEDM 2019
Fundamental limitations of existing models and future solutions for dielectric reliability and RRAM applications (invited)
- Ernest Y. Wu
- Andrew Kim
- et al.
- 2017
- IEDM 2017
Challenges and solutions of FinFET integration in an SRAM cell and a logic circuit for 22 nm node and beyond
- H. Kawasaki
- V.S. Basker
- et al.
- 2009
- IEDM 2009
Demonstration of highly scaled FinFET SRAM cells with high-Κ/metal gate and investigation of characteristic variability for the 32 nm node and beyond
- H. Kawasaki
- M. Khater
- et al.
- 2008
- IEDM 2008
Resistive Memory Process Optimization for High Resistance Switching Toward Scalable Analog Compute Technology for Deep Learning
- Youngseok Kim
- Soon-Cheon Seo
- et al.
- 2021
- IEEE Electron Device Letters
Superior PBTI reliability for SOI FinFET technologies and its physical understanding
- Miaomiao Wang
- Ramachandran Muralidhar
- et al.
- 2013
- IEEE Electron Device Letters
A comparison of short-channel control in planar bulk and fully depleted devices
- Ramachandran Muralidhar
- Jin Cai
- et al.
- 2012
- IEEE Electron Device Letters
Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited)
- Shubham Jain
- Ching-Tzu Chen
- et al.
- 2023
- ISCAS 2023
Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited)
- Martin M. Frank
- Ning Li
- et al.
- 2023
- IRPS 2023