본문 바로가기
로그인

Semiconductor System Lab

FAMILY

Semiconductor System Lab

Through this homepage, we would like to share our sweats, pains,
excitements and experiences with you.

POST DOCTOR INFO

Sangjin Kim

Ph.D. Student

CONTACT INFORMATION

Address

#1233, Dept. of Electrical Engineering and Computer Science (E3-2) KAIST, 373-1, Guseong-dong, Yuseong-gu, Daejeon, 305-701, Republic of Korea

Tel
+82-42-350-8235

Fax
+82-42-350-3410

E-mail
sangjinkim@kaist.ac.kr

Research Interest

- Multicore Processor Architecture 

- Deep Learning Processor

- Intelligent 3D Vision SoC

Education

2021. 3 ~   Ph.D. Student in EE, Korea Advanced Insititue of Science and Technology (KAIST) 

2021. 2      M.S. in EE, Korea Advanced Insititue of Science and Technology (KAIST)

2019. 2      B.S. in EE, Korea Advanced Insititue of Science and Technology (KAIST)

2014. 2      Gwangju  Science High School

BIOGRAPHY

- International Journal Papers  


Scaling-CIM: eDRAM In-Memory-Computing Accelerator With Dynamic-Scaling ADC and Adaptive Analog Operation
Sangjin Kim, Soyeon Um, Wooyoung Jo, Jingu Lee, Sangwoo Ha, Zhiyong Li, and Hoi-Jun Yoo
IEEE Journal of Solid-State Circuits (JSSC), Feb. 2024

An Overview of Computing-in-Memory Circuits With DRAM and NVM
Sangjin Kim, and Hoi-Jun Yoo
IEEE Transactions on Circuits and Systems II (TCAS-II), Nov. 2023

DynaPlasia: An eDRAM In-Memory Computing-Based Reconfigurable Spatial Accelerator With Triple-Mode Cell
Sangjin Kim, Zhiyong Li, Soyeon Um, Wooyoung Jo, Sangwoo Ha, Juhyoung Lee, Sangyeob Kim, Donghyeon Han, and Hoi-Jun Yoo
IEEE Journal of Solid-State Circuits (JSSC), Oct. 2023

A Low-Power Graph Convolutional Network Processor with Sparse Grouping for 3D Point Cloud Semantic Segmentation in Mobile Devices

Sangjin Kim, Sangyeob Kim, Juhyoung Lee, and Hoi-Jun Yoo

IEEE Transactions on Circuits and Systems I (TCAS-I), Jan. 2022


- International Conference Papers


Scaling-CIM: An eDRAM-based In-Memory-Computing Accelerator with Dynamic-Scaling ADC for SQNR-Boosting and Layer-wise Adaptive Bit-Truncation

Sangjin Kim, Soyeon Um, Wooyoung Jo, Jingu Lee, Sangwoo Ha, Zhiyong Li and Hoi-Jun Yoo

IEEE Symposium on VLSI Circuits (S. VLSI), Apr. 2023


DynaPlasia: An eDRAM In-Memory-Computing-Based Reconfigurable Spatial Accelerator with Triple-Mode Cell for Dynamic Resource Switching

Sangjin Kim, Zhiyong Li, Soyeon Um, Wooyoung Jo, Sangwoo Ha, Juhyoung Lee, Sangyeob Kim, and Hoi-Jun Yoo

IEEE International Conference on Solid-State Circuits (ISSCC), Feb. 2023


PNNPU: A Fast and Efficient 3D Point Cloud-based Neural Network Processor with Block-based Point Processing for Regular DRAM Access 

Sangjin Kim, Juhyoung Lee, Dongseok Im, and Hoi-jun Yoo

IEEE Symposium on High Performance Chips (HOT Chips), Aug. 2021


PNNPU: A 11.9 TOPS/W High-speed 3D Point Cloud-based Neural Network Processor with Block-based Point Processing for Regular DRAM Access 

Sangjin Kim, Juhyoung Lee, Dongseok Im, and Hoi-Jun Yoo

IEEE Symposium on VLSI Circuits (S. VLSI), Jun. 2021


A 54.7 fps 3D Point Cloud Semantic Segmentation Processor with Sparse Grouping Based Dilated Graph Convolutional Network for Mobile Devices

Sangjin Kim, Sangyeob Kim, Juhyoung Lee, and Hoi-jun Yoo 

IEEE International Symposium on Circuit and Systems (ISCAS), Oct. 2020

Sangyeob Kim

Ph.D. Student

CONTACT INFORMATION

Address

#1233, Dept. of Electrical Engineering and Computer Science (E3-2) KAIST, 373-1, Guseong-dong, Yuseong-gu, Daejeon, 305-701, Republic of Korea

Tel
+82-42-350-8068

Fax
+82-42-350-3410

E-mail
sangyeob.kim@kaist.ac.kr

Research Interest

- Deep Learning & AI Algorithm

- Machine Learning based SoC Design

Education

2023. 8      Ph.D. Student in EE, Korea Advanced Insititue of Science and Technology (KAIST)

2020. 2      M.S. in EE, Korea Advanced Insititue of Science and Technology (KAIST)

2018. 2      B.S. in EE, Korea Advanced Insititue of Science and Technology (KAIST)

2014. 2      Kyongbuk Science High School

BIOGRAPHY

- International Journal Papers  


C-DNN: An Energy-Efficient Complementary Deep-Neural-Network Processor With Heterogeneous CNN/SNN Core Architecture

Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Donghyeon Han, Jiwon Choi and Hoi-Jun Yoo

IEEE Journal of Solid-State Circuits (JSSC), Nov. 2023

COOL-NPU: Complementary Online Learning Neural Processing Unit
Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Jiwon Choi, Donghyeon Han, and Hoi-Jun Yoo
IEEE MICRO, Nov. 2023

C-DNN V2: Complementary Deep-Neural-Network Processor with Full-Adder/OR-based Reduction Tree and Reconfigurable Spatial Weight Reuse
Sangyeob Kim, and Hoi-Jun Yoo
IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), Oct. 2023

Neuro-CIM: ADC-less Neuromorphic Computing-in-Memory Processor with Operation Gating/Stopping and Digital-Analog Networks
Sangyeob Kim, Sangjin Kim, Soyeon Um, Sangjin Kim, Kwantae Kim and Hoi-Jun Yoo
IEEE Journal of Solid-State Circuits (JSSC), Apr. 2023

SNPU: An Energy-Efficient Spike Domain Deep-Neural-Network Processor with Two-step Spike Encoding and Shift-and-Accumulation Unit
Sangyeob Kim, Sangjin Kim, Soyeon Um, Sangjin Kim, Juhyoung Lee and Hoi-Jun Yoo
IEEE Journal of Solid-State Circuits (JSSC), Apr. 2023

TSUNAMI: Triple Sparsity-aware Ultra Energy-efficient Neural Network Training Accelerator with Multi-modal Iterative Pruning 

Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Donghyeon Han, Wooyoung Jo, and Hoi-Jun Yoo

IEEE Transactions on Circuits and Systems I (TCAS-1), Jan. 2022


PNPU: An Energy-Efficient Deep-Neural-Network Learning Processor With Stochastic Coarse–Fine Level Weight Pruning and Adaptive Input/Output/Weight Zero Skipping

Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Jinmook Lee, Wooyoung Jo, and Hoi-Jun Yoo

IEEE Solid-State Circuits Letters (SSCL), Dec. 2020


A Power-Efficient CNN Accelerator With Similar Feature Skipping for Face Recognition in Mobile Devices 

Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Jinsu Lee, and Hoi-Jun Yoo

IEEE Transactions on Circuits and Systems I (TCAS-1), Jan. 2020


- International Conference Papers


Two-Step Spike Encoding Scheme and Architecture for Highly Sparse Spiking-Neural-Network

Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, and Hoi-Jun Yoo

IEEE International Symposium on Circuits and Systems (ISCAS), May. 2024


C-Transformer: A 2.6-18.1μJ/Token Homogeneous DNN-Transformer/Spiking-Transformer Processor with Big-Little Network and Implicit Weight Generation for Large Language Models

Sangyeob Kim, Sangjin Kim, Wooyoung Jo, Soyeon Kim, Seongyon Hong, and Hoi-Jun Yoo

IEEE International Conference on Solid-State Circuits (ISSCC), Feb. 2024


COOL-NPU: Complementary Online Learning Neural Processing Unit with CNN-SNN Heterogeneous Core and Event-driven Backpropagation

Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Donghyeon Han, Jiwon Choi, and Hoi-Jun Yoo

IEEE Symposium on Low-Power and High-Speed Chips (COOL Chips), Mar. 2023


C-DNN: A 24.5-to-85.8TOPS/W Complementary-Deep-Neural-Network Processor with Heterogeneous CNN/SNN Core Architecture and Forward-Gradient-based Sparsity Generation

Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Donghyeon Han, and Hoi-Jun Yoo

IEEE International Conference on Solid-State Circuits (ISSCC), Feb. 2023


SNPU: Always-on 63.2uW Face Recognition Spike Domain Convolutional Neural Network Processor with Spike Train Decomposition and Shift-and-Accumulation

Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Juhyoung Lee, and Hoi-Jun Yoo

IEEE Asian Solid-State Circuits Conference (A-SSCC), Nov. 2022


Neuro-CIM: A 310.4TOPS/W Neuromorphic Computing-in-Memory Processor with Low WL/BL activity and Digital-Analog Mixed-mode Neuron Firing 

Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Kwantae Kim, and Hoi-Jun Yoo

IEEE Symposium on High Performance Chips (HOT Chips), Aug. 2022


Neuro-CIM: A 310.4TOPS/W Neuromorphic Computing-in-Memory Processor with Low WL/BL activity and Digital-Analog Mixed-mode Neuron Firing 

Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Kwantae Kim, and Hoi-Jun Yoo

Symposium on VLSI Circuits (S. VLSI), Jun. 2022


PNPU: A 146.52TOPS/W Deep-Neural-Network Learning Processor with Stochastic Coarse-Fine Pruning and Adaptive Input/Output/Weight Skipping 

Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Jinmook Lee, and Hoi-Jun Yoo

Symposium on VLSI Circuits (S. VLSI), Jun. 2020


A 15.2 TOPS/W CNN Accelerator with Similar Feature Skipping for Face Recognition in Mobile Devices

Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Jinsu Lee, and Hoi-Jun Yoo

IEEE International Symposium on Circuit and Systems (ISCAS), May. 2019

Dongseok Im

Ph.D. Student

CONTACT INFORMATION

Address

#1233, Dept. of Electrical Engineering and Computer Science (E3-2) KAIST, 373-1, Guseong-dong, Yuseong-gu, Daejeon, 305-701, Republic of Korea

Tel
+82-42-350-8068

Fax
+82-42-350-3410

E-mail
dsim@kaist.ac.kr

Research Interest

- Energy-efficient Deep Learning SoC Design

- Intelligent Vision System Development


Education

2023. 8      Ph.D. Student in EE, Korea Advanced Insititue of Science and Technology (KAIST)

2020. 2      M.S. in EE, Korea Advanced Insititue of Science and Technology (KAIST)

2018. 2      B.S. in EE, POSTECH

2014. 2      Jamsil High School

BIOGRAPHY

- International Journal Papers   


A Mobile 3D Object Recognition Processor with Deep Learning-based Monocular Depth Estimation

Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, and Hoi-Jun Yoo

IEEE MICRO, Mar. 2023


DSPU: An Efficient Deep Learning-Based Dense RGB-D Data Acquisition with Sensor Fusion and 3-D Perception SoC  

Dongseok Im, Gwangtae Park, Junha Ryu, Zhiyong Li, Sanghoon Kang, Donghyeon Han, Junsu Lee, Wonhoon Park, Hankyul Kwon, and Hoi-Jun Yoo

IEEE Journal of Solid-State Circuits (JSSC), 2022


A Pipelined Point Cloud based Neural Network Processor for 3D Vision with Large-scale Max Pooling Layer Prediction

Dongseok Im, Donghyeon Han, Sanghoon Kang, and Hoi-Jun Yoo

IEEE Journal of Solid-State Circuits (JSSC), Jun. 2021


DT-CNN: An Energy-Efficient Dilated and Transposed Convolutional Neural Network Processor for Region of Interest Based Image Segmentation 

Dongseok Im, Donghyeon Han, Sungpill Choi, Sanghoon Kang, and Hoi-Jun Yoo

IEEE Transactions on Circuits and Systems I (TCAS-1), May. 2020


- International Conference Papers


Sibia: Signed Bit-slice Architecture for Dense DNN Acceleration with Slice-level Sparsity Exploitation 

Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, and Hoi-Jun Yoo

IEEE International Symposium on High-Performance Computer Architecture (HPCA), Feb. 2023


DSPU: A 281.6mW Real-Time Deep Learning- Based Dense RGB-D Data Acquisition with Sensor Fusion and 3D Perception System-on-Chip  

Dongseok Im, Gwangtae Park, Junha Ryu, Zhiyong Li, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, and Hoi-Jun Yoo

IEEE Symposium on High Performance Chips (HOT Chips), Aug. 2022


​A Low-power and Real-time 3D Object Recognition Processor with Dense RGB-D Data Acquisition in Mobile Platforms 

Dongseok Im, Gwangtae Park, Junha Ryu, Zhiyong Li, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, and Hoi-Jun Yoo

IEEE Symposium on Low-Power and High-Speed Chips (COOL Chips), Apr. 2022


​DSPU: A 281.6mW Real-Time Depth Signal Processing Unit for Deep Learning- Based Dense RGB-D Data Acquisition with Depth Fusion and 3D Bounding Box Extraction in Mobile Platforms

Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, and Hoi-Jun Yoo

International Solid-State Circuits Conference (ISSCC), Feb. 2022


A 4.45 ms Low-latency 3D Point-cloud-based Neural Network Processor for Hand Pose Estimation in Immersive Wearable Devices 

Dongseok Im, Sanghoon Kang, Donghyeon Han, Sungpill Choi, and Hoi-Jun Yoo

Symposium on VLSI Circuits (S. VLSI), Jun. 2020


DT-CNN: Dilated and Transposed Convolution Neural Network Accelerator for Real-time Image Segmentation on Mobile Devices 

Dongseok Im, Donghyeon Han, Sungpill Choi, Sanghoon Kang, and Hoi-Jun Yoo

IEEE International Symposium on Circuit and Systems (ISCAS), May. 2019

Address#1233, School of Electrical Engineering, KAIST, 291 Daehak-ro (373-1 Guseong-dong), Yuseong-gu, Daejeon 34141, Republic of Korea
Tel +82-42-350-8068 Fax +82-42-350-3410E-mail sslmaster@kaist.ac.kr·© SSL. All Rights Reserved.·Design by NSTAR