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ORCIDSangwoo Jung 0001
Person information
- affiliation: Korea University, School of Electrical Engineering, Seoul, Korea
- affiliation: Samsung Electronics, Foundry Division, Hwaseong, Korea
- affiliation (PhD 2025): Daegu Gyeongbuk Institute of Science and Technology (DGIST), Department of electrical engineering and computer science, Daegu, Korea
Other persons with the same name
- Sangwoo Jung 0002
![[0000-0003-0187-006X]](https://devdomain4test.ir/img/orcid-mark.12x12.png "0000-0003-0187-006X")
— Seoul National University (SNU), Department of Mechanical Engineering, Korea - Sangwoo Jung 0003 — Chungnam National University, Department of Computer Science and Engineering, Korea
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2020 – today
- 2026
[j3]Sangwoo Jung, Hojin Lee, Jiyong Park, Yejin Lee, Dahoon Park, Hyunseob Shin, Jong-Hyeok Yoon, Jaeha Kung:
A Hybrid Digital-Analog Compute-in-Memory Using Content-Addressable Memory With Flexible Multi-Bit Slicing. IEEE Trans. Circuits Syst. I Regul. Pap. 73(5): 3452-3465 (2026)- [j2]Jooyeon Lee, Sangwoo Jung, Jaeha Kung:
Fused-STA: Automated Design Space Exploration of a Fused Systolic Tensor Array for Universal Deep Learning Acceleration. IEEE Trans. Very Large Scale Integr. Syst. 34(8): 2355-2368 (2026) - 2025
- [c8]Gunil Kang, Dahoon Park, Hojin Lee, Sangwoo Jung, Jiyong Park, Jung Gyu Min, Youngjoo Lee, Jaeha Kung:
RISC-V Driven Orchestration of Vector Processing Units and eFlash Compute-in-Memory Arrays for Fast and Accurate Keyword Spotting. ASP-DAC 2025: 1174-1180 - [c7]Yongjoo Jang, Sangwoo Hwang, Hojin Lee, Sangwoo Jung, Donghun Lee, Wonbo Shim, Jaeha Kung:
Dissecting and Re-Architecting 3D NAND Flash PIM Arrays for Efficient Single-Batch Token Generation in LLMS. ICCD 2025: 237-244 - [c6]Sangwoo Jung, Hojin Lee, Yejin Lee, Jiyong Park, Dahoon Park, Hyunseob Shin, Jong-Hyeok Yoon, Jaeha Kung:
CAM-CIM: A Hybrid Compute-in-Memory Using Content-Addressable Memory with Subword Split Mapping for Reduced ADC Resolution. ISLPED 2025: 1-7 - [i2]Yongjoo Jang, Sangwoo Hwang, Hojin Lee, Sangwoo Jung, Donghun Lee, Wonbo Shim, Jaeha Kung:
Dissecting and Re-architecting 3D NAND Flash PIM Arrays for Efficient Single-Batch Token Generation in LLMs. CoRR abs/2511.12860 (2025) - 2024
- [j1]Sangwoo Jung, Jaehyun Lee, Dahoon Park, Youngjoo Lee, Jong-Hyeok Yoon, Jaeha Kung:
A Dual-Precision and Low-Power CNN Inference Engine Using a Heterogeneous Processing-in-Memory Architecture. IEEE Trans. Circuits Syst. I Regul. Pap. 71(12): 5546-5559 (2024) - [c5]Jeongyoon Wie, Sangwoo Jung, Taeryoung Seol, Geunha Kim, Sehwan Lee, Homin Jang, Samhwan Kim, Yeonjae Shin, Jae Eun Jang, Jaeha Kung, Arup K. George, Junghyup Lee:
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. CICC 2024: 1-2 - [c4]Jahyun Koo, Dahoon Park, Sangwoo Jung, Jaeha Kung:
OPAL: Outlier-Preserved Microscaling Quantization Accelerator for Generative Large Language Models. DAC 2024: 259:1-259:6 - [i1]Jahyun Koo, Dahoon Park, Sangwoo Jung, Jaeha Kung:
OPAL: Outlier-Preserved Microscaling Quantization Accelerator for Generative Large Language Models. CoRR abs/2409.05902 (2024) - 2022
- [c3]Sangwoo Jung, Jaehyun Lee, Huiseong Noh, Jong-Hyeok Yoon, Jaeha Kung:
DualPIM: A Dual-Precision and Low-Power CNN Inference Engine Using SRAM- and eDRAM-based Processing-in-Memory Arrays. AICAS 2022: 70-73
2010 – 2019
- 2019
- [c2]Sangwoo Jung, Seungsik Moon, Youngjoo Lee, Jaeha Kung:
WMixNet: An Energy-Scalable and Computationally Lightweight Deep Learning Accelerator. ISLPED 2019: 1-6 - [c1]Sangwoo Jung, Jaeha Kung:
Noise Tolerance of an Energy-Scalable Deep Learning Model with Two Extreme Bit-Precisions. ISOCC 2019: 71-72
Coauthor Index
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