Fault-free: A Fault-resilient Deep Neural Network Accelerator based on Realistic ReRAM Devices
Author:
Funder
National Research Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9585997/9586083/09586286.pdf?arnumber=9586286
Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Harnessing RRAM Technology for Efficient AI Implementation;Recent Advances in Neuromorphic Computing [Working Title];2024-09-02
2. Compute-in-Memory-Based Neural Network Accelerators for Safety-Critical Systems: Worst-Case Scenarios and Protections;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2024-08
3. CRPIM: An efficient compute-reuse scheme for ReRAM-based Processing-in-Memory DNN accelerators;Journal of Systems Architecture;2024-08
4. Efficient Optimized Testing of Resistive RAM Based Convolutional Neural Networks;2024 IEEE 30th International Symposium on On-Line Testing and Robust System Design (IOLTS);2024-07-03
5. Signature Driven Post-Manufacture Testing and Tuning of RRAM Spiking Neural Networks for Yield Recovery;2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC);2024-01-22
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