Je-Min Hung

Challenges and Trends of SRAM-Based Computing-In-Memory for AI Edge Devices

Chuan-Jia Jhang, Cheng-Xin Xue, Je-Min Hung et al. · IEEE Transactions on Circuits and Systems I Regular Papers · 2021 · 245 citations

Engineering, Edge Device, Computer Architecture +18

16.1 A 22nm 4Mb 8b-Precision ReRAM Computing-in-Memory Macro with 11.91 to 195.7TOPS/W for Tiny AI Edge Devices

Cheng-Xin Xue, Je-Min Hung, Hui-Yao Kao et al. · 2021 · 174 citations

Engineering, Energy Efficiency, Emerging Memory Technology +21

A CMOS-integrated compute-in-memory macro based on resistive random-access memory for AI edge devices

Cheng-Xin Xue, Yen-Cheng Chiu, Ta-Wei Liu et al. · Nature Electronics · 2020 · 155 citations

Hardware Security, Engineering, Vlsi Architecture +11

An 8-Mb DC-Current-Free Binary-to-8b Precision ReRAM Nonvolatile Computing-in-Memory Macro using Time-Space-Readout with 1286.4-21.6TOPS/W for Edge-AI Devices

Je-Min Hung, Yen-Hsiang Huang, Sheng-Po Huang et al. · 2022 IEEE International Solid- State Circuits Conference (ISSCC) · 2022 · 112 citations

Non-volatile Memory, Engineering, Computer Architecture +19

A four-megabit compute-in-memory macro with eight-bit precision based on CMOS and resistive random-access memory for AI edge devices

Je-Min Hung, Cheng-Xin Xue, Hui-Yao Kao et al. · Nature Electronics · 2021 · 107 citations

Hardware Security, Four-megabit Compute-in-memory Macro, Engineering +13