A full-stack memristor-based computation-in-memory system with software-hardware co-development
Ruihua Yu(Tsinghua University), Huaqiang Wu(Beijing Advanced Sciences and Innovation Center), Jianshi Tang(Tsinghua University), Bin Gao(Chinese Academy of Sciences), Zhenqi Hao(Tsinghua University), Qingtian Zhang(Tsinghua University), Sanchuan Ding(Tsinghua University), Peng Yao(Tsinghua University), Qi Liu(Beijing University of Posts and Telecommunications), Tao Guo(Tsinghua University), He Qian(University of Science and Technology of China), Qi Qin(Tsinghua University), Junyang Zhang(Mongolian University of Science and Technology), Dong Wu(Tsinghua University), Ze Wang(Zhejiang University of Technology)
Cited by 20
Related Papers
Fully hardware-implemented memristor convolutional neural network
|Nature|2020|2.2k
Switching of perpendicular magnetization by spin–orbit torques in the absence of external magnetic fields
|Nature Nanotechnology|2014|1k
Face classification using electronic synapses
|Nature Communications|2017|909
Neuro-inspired computing chips
|Nature Electronics|2020|886
A compute-in-memory chip based on resistive random-access memory
|Nature|2022|882