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2020 – today
- 2024
[j2]Fan Zhang
, Amitesh Sridharan, Wangxin He, Injune Yeo, Maximilian Liehr, Wei Zhang, Nathaniel C. Cady, Yu Cao, Jae-Sun Seo, Deliang Fan:
A 65-nm RRAM Compute-in-Memory Macro for Genome Processing. IEEE J. Solid State Circuits 59(7): 2093-2104 (2024)- 2023
- [c4]Wangxin He, Jian Meng, Sujan Kumar Gonugondla, Shimeng Yu, Naresh R. Shanbhag, Jae-sun Seo:
PRIVE: Efficient RRAM Programming with Chip Verification for RRAM-based In-Memory Computing Acceleration. DATE 2023: 1-6 - [c3]Fan Zhang, Wangxin He, Injune Yeo, Maximilian Liehr, Nathaniel C. Cady, Yu Cao, Jae-Sun Seo, Deliang Fan:
A 65nm RRAM Compute-in-Memory Macro for Genome Sequencing Alignment. ESSCIRC 2023: 117-120 - 2021
- [c2]Wangxin He, Wonbo Shim, Shihui Yin, Xiaoyu Sun, Deliang Fan, Shimeng Yu, Jae-sun Seo:
Characterization and Mitigation of Relaxation Effects on Multi-level RRAM based In-Memory Computing. IRPS 2021: 1-7 - [c1]Vinay Joshi, Wangxin He, Jae-sun Seo, Bipin Rajendran:
Hybrid In-Memory Computing Architecture for the Training of Deep Neural Networks. ISCAS 2021: 1-5 - [i1]Vinay Joshi, Wangxin He, Jae-sun Seo, Bipin Rajendran:
Hybrid In-memory Computing Architecture for the Training of Deep Neural Networks. CoRR abs/2102.05271 (2021)
2010 – 2019
- 2019
- [j1]Shihui Yin, Jae-sun Seo, Yulhwa Kim, Xu Han, Hugh J. Barnaby, Shimeng Yu, Yandong Luo, Wangxin He, Xiaoyu Sun, Jae-Joon Kim:
Monolithically Integrated RRAM- and CMOS-Based In-Memory Computing Optimizations for Efficient Deep Learning. IEEE Micro 39(6): 54-63 (2019)
Coauthor Index
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