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Showing results 1 to 6 of 6

Conference
A 3.3-To-11V-Supply-Range 10μW/Ch Arbitrary-Waveform-Capable Neural Stimulator with Output-Adaptive-Self-Bias and Supply-Tracking Schemes in 0.18μm Standard CMOS
  • Wie, Jeongyoon ; 
  • Jung, Sangwoo ; 
  • Seol, Taeryoung ; 
  • Kim, Geunha ; 
  • Lee, Sehwan ; 
  • Jang, Homin ; 
  • Kim, Samhwan ; 
  • Shin, Yeon Jae ; 
  • Jang, Jae Eun ; 
  • Kung, Jaeha ; 
    • et al
  • 2024-04-24
  • Wie, Jeongyoon. (2024-04-24). A 3.3-To-11V-Supply-Range 10μW/Ch Arbitrary-Waveform-Capable Neural Stimulator with Output-Adaptive-Self-Bias and Supply-Tracking Schemes in 0.18μm Standard CMOS. 44th Annual IEEE Custom Integrated Circuits Conference, CICC 2024, 1–2. doi: 10.1109/CICC60959.2024.10529100
  • IEEE Solid-State Circuits Society
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Article
A Dual-Precision and Low-Power CNN Inference Engine Using a Heterogeneous Processing-in-Memory Architecture
  • Jung, Sangwoo ; 
  • Lee, Jaehyun ; 
  • Park, Dahoon ; 
  • Lee, Youngjoo ; 
  • Yoon, Jong-Hyeok ; 
  • Kung, Jaeha
  • 2024-12
  • Jung, Sangwoo. (2024-12). A Dual-Precision and Low-Power CNN Inference Engine Using a Heterogeneous Processing-in-Memory Architecture. IEEE Transactions on Circuits and Systems I: Regular Papers, 71(12), 5546–5559. doi: 10.1109/TCSI.2024.3395842
  • Institute of Electrical and Electronics Engineers
  • View : 191
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Conference
DualPIM: A Dual-Precision and Low-Power CNN Inference Engine Using SRAM- and eDRAM-based Processing-in-Memory Arrays
  • 2022-06-14
  • Jung, Sangwoo. (2022-06-14). DualPIM: A Dual-Precision and Low-Power CNN Inference Engine Using SRAM- and eDRAM-based Processing-in-Memory Arrays. 4th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022, 70–73. doi: 10.1109/AICAS54282.2022.9869905
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 191
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Conference
Noise Tolerance of an Energy-Scalable Deep Learning Model with Two Extreme Bit-Precisions
  • 2019-10-07
  • Jung, Sangwoo. (2019-10-07). Noise Tolerance of an Energy-Scalable Deep Learning Model with Two Extreme Bit-Precisions. International System-on-Chip Design Conference, ISOCC 2019, 71–72. doi: 10.1109/ISOCC47750.2019.9078497
  • Institute of Semiconductor Engineers of Korea (반도체공학회), IEEE Circuits and Systems (CAS) Society
  • View : 380
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Conference
OPAL: Outlier-Preserved Microscaling Quantization Accelerator for Generative Large Language Models
  • Koo, Jahyun ; 
  • Park, Dahoon ; 
  • Jung, Sangwoo ; 
  • Kung, Jaeha
  • 2024-06-25
  • Koo, Jahyun. (2024-06-25). OPAL: Outlier-Preserved Microscaling Quantization Accelerator for Generative Large Language Models. Design Automation Conference, 1–6. doi: 10.1145/3649329.3657323
  • Institute of Electrical and Electronics Engineers Inc.
  • View : 63
  • Download : 0
Conference
RISC-V Driven Orchestration of Vector Processing Units and eFlash Compute-in-Memory Arrays for Fast and Accurate Keyword Spotting
  • Kang, Gunil ; 
  • Park, Dahoon ; 
  • Lee, Hojin ; 
  • Jung, Sangwoo ; 
  • Park, Jiyong ; 
  • Min, Jung Gyu ; 
  • Lee, Youngjoo ; 
  • Kung, Jaeha
  • 2025-01-23
  • Kang, Gunil. (2025-01-23). RISC-V Driven Orchestration of Vector Processing Units and eFlash Compute-in-Memory Arrays for Fast and Accurate Keyword Spotting. 30th Asia and South Pacific Design Automation Conference, ASP-DAC 2025, 1174–1180. doi: 10.1145/3658617.3697697
  • Association for Computing Machinery
  • View : 231
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