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Disambiguation of "Khwa, Win-San"

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Parallelizing SRAM arrays with customized bit-cell for binary neural networks.

, , , , , , , , and . DAC, page 21:1-21:6. ACM, (2018)

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San San Lin

San San Hmwe

Abdul Hamied Khwaja

Thein Win

Zaw Win

 

Other publications of authors with the same name

8-b Precision 8-Mb ReRAM Compute-in-Memory Macro Using Direct-Current-Free Time-Domain Readout Scheme for AI Edge Devices., , , , , , , , , and 4 other author(s). IEEE J. Solid State Circuits, 58 (1): 303-315 (2023)A 5.1pJ/Neuron 127.3us/Inference RNN-based Speech Recognition Processor using 16 Computing-in-Memory SRAM Macros in 65nm CMOS., , , , , , , , , and 3 other author(s). VLSI Circuits, page 120-. IEEE, (2019)High-density analog image storage in an analog-valued non-volatile memory array., , , , , , and . Neuromorph. Comput. Eng., 2 (4): 44018 (December 2022)30.1 A 40nm VLIW Edge Accelerator with 5MB of 0.256pJ/b RRAM and a Localization Solver for Bristle Robot Surveillance., , , , , , , , , and 2 other author(s). ISSCC, page 482-484. IEEE, (2024)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)A 22nm 8Mb STT-MRAM Near-Memory-Computing Macro with 8b-Precision and 46.4-160.1TOPS/W for Edge-AI Devices., , , , , , , , , and 8 other author(s). ISSCC, page 496-497. IEEE, (2023)Circuit design for beyond von Neumann applications using emerging memory: From nonvolatile logics to neuromorphic computing., , , , , , , , , and . ISQED, page 23-28. IEEE, (2017)A 40-nm 118.44-TOPS/W Voltage-Sensing Compute-in-Memory RRAM Macro With Write Verification and Multi-Bit Encoding., , , , , and . IEEE J. Solid State Circuits, 57 (3): 845-857 (2022)A 40-nm, 64-Kb, 56.67 TOPS/W Voltage-Sensing Computing-In-Memory/Digital RRAM Macro Supporting Iterative Write With Verification and Online Read-Disturb Detection., , , , , and . IEEE J. Solid State Circuits, 57 (1): 68-79 (2022)A 28nm Nonvolatile AI Edge Processor using 4Mb Analog-Based Near-Memory-Compute ReRAM with 27.2 TOPS/W for Tiny AI Edge Devices., , , , , , , , , and 8 other author(s). VLSI Technology and Circuits, page 1-2. IEEE, (2023)