3 papers
cs.ET2025
First Demonstration of Second-order Training of Deep Neural Networks with In-memory Analog Matrix Computing
Saitao Zhang, Yubiao Luo, Shiqing Wang +5
Second-order optimization methods, which leverage curvature information, offer faster and more stable convergence than first-order methods such as stochastic gradient descent (SGD)…
cs.AR2025
GRAMC: General-purpose and reconfigurable analog matrix computing architecture
Lunshuai Pan, Shiqing Wang, Pushen Zuo +1
In-memory analog matrix computing (AMC) with resistive random-access memory (RRAM) represents a highly promising solution that solves matrix problems in one step. However, the exis…
cs.ET2024
The maximum storage capacity of open-loop written RRAM is around 4 bits
Yongxiang Li, Shiqing Wang, Zhong Sun
There have been a plethora of research on multi-level memory devices, where the resistive random-access memory (RRAM) is a prominent example. Although it is easy to write an RRAM d…