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ORCIDSangjin Kim
- > Home > Persons > Sangjin Kim
Publications
- 2024
[j43]Sangjin Kim
, Zhiyong Li, Soyeon Um, Wooyoung Jo, Sangwoo Ha, Juhyoung Lee, Sangyeob Kim, Donghyeon Han, Hoi-Jun Yoo:
DynaPlasia: An eDRAM In-Memory Computing-Based Reconfigurable Spatial Accelerator With Triple-Mode Cell. IEEE J. Solid State Circuits 59(1): 102-115 (2024)- 2023
- [j33]Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Juhyoung Lee, Hoi-Jun Yoo:
SNPU: An Energy-Efficient Spike Domain Deep-Neural-Network Processor With Two-Step Spike Encoding and Shift-and-Accumulation Unit. IEEE J. Solid State Circuits 58(10): 2812-2825 (2023) - [c63]Sangjin Kim, Zhiyong Li, Soyeon Um, Wooyoung Jo, Sangwoo Ha, Juhyoung Lee, Sangyeob Kim, Donghyeon Han, Hoi-Jun Yoo:
DynaPlasia: An eDRAM In-Memory-Computing-Based Reconfigurable Spatial Accelerator with Triple-Mode Cell for Dynamic Resource Switching. ISSCC 2023: 256-257 - [c61]Wooyoung Jo, Sangjin Kim, Juhyoung Lee, Donghyeon Han, Sangyeob Kim, Seungyoon Choi, Hoi-Jun Yoo:
NeRPIM: A 4.2 mJ/frame Neural Rendering Processing-in-memory Processor with Space Encoding Block-wise Mapping for Mobile Devices. VLSI Technology and Circuits 2023: 1-2 - 2022
- [j28]Juhyoung Lee, Sangyeob Kim, Sangjin Kim, Wooyoung Jo, Ji-Hoon Kim, Donghyeon Han, Hoi-Jun Yoo:
OmniDRL: An Energy-Efficient Deep Reinforcement Learning Processor With Dual-Mode Weight Compression and Sparse Weight Transposer. IEEE J. Solid State Circuits 57(4): 999-1012 (2022) - [j27]Juhyoung Lee, Jihoon Kim, Wooyoung Jo, Sangyeob Kim, Sangjin Kim, Hoi-Jun Yoo:
ECIM: Exponent Computing in Memory for an Energy-Efficient Heterogeneous Floating-Point DNN Training Processor. IEEE Micro 42(1): 99-107 (2022) - [j26]Sangjin Kim, Sangyeob Kim, Juhyoung Lee, Hoi-Jun Yoo:
A Low-Power Graph Convolutional Network Processor With Sparse Grouping for 3D Point Cloud Semantic Segmentation in Mobile Devices. IEEE Trans. Circuits Syst. I Regul. Pap. 69(4): 1507-1518 (2022) - 2021
- [c52]Juhyoung Lee, Changhyeon Kim, Donghyeon Han, Sangyeob Kim, Sangjin Kim, Hoi-Jun Yoo:
Energy-Efficient Deep Reinforcement Learning Accelerator Designs for Mobile Autonomous Systems. AICAS 2021: 1-4 - [c51]Sangjin Kim, Juhyoung Lee, Dongseok Im, Hoi-Jun Yoo:
PNNPU: A Fast and Efficient 3D Point Cloud-based Neural Network Processor with Block-based Point Processing for Regular DRAM Access. HCS 2021: 1-23 - [c50]Juhyoung Lee, Jihoon Kim, Wooyoung Jo, Sangyeob Kim, Sangjin Kim, Donghyeon Han, Jinsu Lee, Hoi-Jun Yoo:
An Energy-efficient Floating-Point DNN Processor using Heterogeneous Computing Architecture with Exponent-Computing-in-Memory. HCS 2021: 1-20 - [c49]Juhyoung Lee, Sangyeob Kim, Ji-Hoon Kim, Sangjin Kim, Wooyoung Jo, Donghyeon Han, Hoi-Jun Yoo:
OmniDRL: An Energy-Efficient Mobile Deep Reinforcement Learning Accelerators with Dual-mode Weight Compression and Direct Processing of Compressed Data. HCS 2021: 1-21 - [c48]Sangjin Kim, Juhyoung Lee, Dongseok Im, Hoi-Jun Yoo:
PNNPU: A 11.9 TOPS/W High-speed 3D Point Cloud-based Neural Network Processor with Block-based Point Processing for Regular DRAM Access. VLSI Circuits 2021: 1-2 - [c47]Juhyoung Lee, Jihoon Kim, Wooyoung Jo, Sangyeob Kim, Sangjin Kim, Jinsu Lee, Hoi-Jun Yoo:
A 13.7 TFLOPS/W Floating-point DNN Processor using Heterogeneous Computing Architecture with Exponent-Computing-in-Memory. VLSI Circuits 2021: 1-2 - [c46]Juhyoung Lee, Sangyeob Kim, Sangjin Kim, Wooyoung Jo, Donghyeon Han, Jinsu Lee, Hoi-Jun Yoo:
OmniDRL: A 29.3 TFLOPS/W Deep Reinforcement Learning Processor with Dualmode Weight Compression and On-chip Sparse Weight Transposer. VLSI Circuits 2021: 1-2 - [i1]Juhyoung Lee, Sangyeob Kim, Sangjin Kim, Wooyoung Jo, Hoi-Jun Yoo:
GST: Group-Sparse Training for Accelerating Deep Reinforcement Learning. CoRR abs/2101.09650 (2021) - 2020
- [c44]Sangjin Kim, Sangyeob Kim, Juhyoung Lee, Hoi-Jun Yoo:
A 54.7 fps 3D Point Cloud Semantic Segmentation Processor with Sparse Grouping Based Dilated Graph Convolutional Network for Mobile Devices. ISCAS 2020: 1-5
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