A full-stack memristor-based computation-in-memory system with software-hardware co-development
Abstract The practicality of memristor-based computation-in-memory (CIM) systems is limited by the specific hardware design and the manual parameters tuning process. Here, we introduce a software-hardware co-development approach to improve the flexibility and efficiency of the CIM system. The hardwa...
Saved in:
| Main Authors: | Ruihua Yu, Ze Wang, Qi Liu, Bin Gao, Zhenqi Hao, Tao Guo, Sanchuan Ding, Junyang Zhang, Qi Qin, Dong Wu, Peng Yao, Qingtian Zhang, Jianshi Tang, He Qian, Huaqiang Wu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-57183-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Thermal Analysis and Evaluation of Memristor-Based Compute-in-Memory Chips
by: Awang Ma, et al.
Published: (2025-03-01) -
Hardware Implementation of Memristor Ratioed Logic Circuits Based on Egg Protein Memristors
by: Lu Wang, et al.
Published: (2025-05-01) -
Ultra robust negative differential resistance memristor for hardware neuron circuit implementation
by: Yifei Pei, et al.
Published: (2025-01-01) -
Heterogeneous integration of 2D memristor arrays and silicon selectors for compute-in-memory hardware in convolutional neural networks
by: Samarth Jain, et al.
Published: (2025-03-01) -
Memristor-Based Artificial Neural Networks for Hardware Neuromorphic Computing
by: Boyan Jin, et al.
Published: (2025-01-01)