3 papers
cs.AR2026
An Emerging NVM-Based On-Chip Training Architecture with Non-Ideality Mitigation Through Bipolar Weight Distributions
Peng Dang, Youna Huang, Yintao He +1
The rapid advancement of deep learning has presented significant energy efficiency challenges to the conventional von Neumann architecture. In-memory computing (IMC) architectures…
cs.AR2026
VARA: A Voltage-Aware ReRAM-Based Accelerator for Energy-Efficient Computing
Peng Dang, Yintao He, Huawei Li
ReRAM-based in-memory computing (IMC) architectures are widely regarded as a promising approach to alleviating the computational bottleneck of conventional architectures. Since ReR…
cs.AR2024
A Fully Hardware Implemented Accelerator Design in ReRAM Analog Computing without ADCs
Peng Dang, Huawei Li, Wei Wang
Emerging ReRAM-based accelerators process neural networks via analog Computing-in-Memory (CiM) for ultra-high energy efficiency. However, significant overhead in peripheral circuit…