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Disambiguation of "Xue, Cheng-Xin"

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A 65nm 1Mb nonvolatile computing-in-memory ReRAM macro with sub-16ns multiply-and-accumulate for binary DNN AI edge processors.

, , , , , , , , , , , , , , , , and . ISSCC, page 494-496. IEEE, (2018)

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Cheng Xue

Xue-Xin Liu

Xue Xue Zhang

Jia Xue

Min Xue

 

Other publications of authors with the same name

Embedded 1-Mb ReRAM-Based Computing-in- Memory Macro With Multibit Input and Weight for CNN-Based AI Edge Processors., , , , , , , , , and 10 other author(s). IEEE J. Solid State Circuits, 55 (1): 203-215 (2020)Challenges in Circuit Designs of Nonvolatile-memory based computing-in-memory for AI Edge Devices., and . ISOCC, page 164-165. IEEE, (2019)15.4 A 22nm 2Mb ReRAM Compute-in-Memory Macro with 121-28TOPS/W for Multibit MAC Computing for Tiny AI Edge Devices., , , , , , , , , and 10 other author(s). ISSCC, page 244-246. IEEE, (2020)A 12-nm 0.62-1.61 mW Ultra-Low Power Digital CIM-based Deep-Learning System for End-to-End Always-on Vision., , , , , , , , , and 7 other author(s). VLSI Technology and Circuits, page 1-2. IEEE, (2023)A 22nm 4Mb 8b-Precision ReRAM Computing-in-Memory Macro with 11.91 to 195.7TOPS/W for Tiny AI Edge Devices., , , , , , , , , and 8 other author(s). ISSCC, page 245-247. IEEE, (2021)Challenges and Trends of SRAM-Based Computing-In-Memory for AI Edge Devices., , , , and . IEEE Trans. Circuits Syst. I Regul. Pap., 68 (5): 1773-1786 (2021)A 28-nm 320-Kb TCAM Macro Using Split-Controlled Single-Load 14T Cell and Triple-Margin Voltage Sense Amplifier., , , , , and . IEEE J. Solid State Circuits, 54 (10): 2743-2753 (2019)33.2 A Fully Integrated Analog ReRAM Based 78.4TOPS/W Compute-In-Memory Chip with Fully Parallel MAC Computing., , , , , , , , , and 5 other author(s). ISSCC, page 500-502. IEEE, (2020)A 22-nm 1-Mb 1024-b Read Data-Protected STT-MRAM Macro With Near-Memory Shift-and-Rotate Functionality and 42.6-GB/s Read Bandwidth for Security-Aware Mobile Device., , , , , , , , , and 7 other author(s). IEEE J. Solid State Circuits, 57 (6): 1936-1949 (2022)A 12nm 137 TOPS/W Digital Compute-In-Memory using Foundry 8T SRAM Bitcell supporting 16 Kernel Weight Sets for AI Edge Applications., , , , , , , , , and 1 other author(s). VLSI Technology and Circuits, page 1-2. IEEE, (2023)