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Sangyeob Kim
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2020 – today
- 2024
- [j20]Jonathan Derot, Nozomi Sugiura, Sangyeob Kim, Shinya Kouketsu:
Improved climate time series forecasts by machine learning and statistical models coupled with signature method: A case study with El Niño. Ecol. Informatics 79: 102437 (2024) - [j19]Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, Jongjun Park, Hoi-Jun Yoo:
MetaVRain: A Mobile Neural 3-D Rendering Processor With Bundle-Frame-Familiarity-Based NeRF Acceleration and Hybrid DNN Computing. IEEE J. Solid State Circuits 59(1): 65-78 (2024) - [j18]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) - [j17]Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Donghyeon Han, Jiwon Choi, Hoi-Jun Yoo:
C-DNN: An Energy-Efficient Complementary Deep-Neural-Network Processor With Heterogeneous CNN/SNN Core Architecture. IEEE J. Solid State Circuits 59(1): 157-172 (2024) - [j16]Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, Jongjun Park, Hoi-Jun Yoo:
A Low-Power Artificial-Intelligence-Based 3-D Rendering Processor With Hybrid Deep Neural Network Computing. IEEE Micro 44(1): 17-27 (2024) - [j15]Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Jiwon Choi, Donghyeon Han, Hoi-Jun Yoo:
COOL-NPU: Complementary Online Learning Neural Processing Unit. IEEE Micro 44(1): 28-37 (2024) - [c33]Seongyon Hong, Sangyeob Kim, Soyeon Kim, Hoi-Jun Yoo:
DualNet: Efficient Integration of Artificial Neural Network and Spiking Neural Network with Equivalent Conversion. AICAS 2024: 100-104 - [c32]Sangjin Kim, Zhiyong Li, Soyeon Um, Wooyoung Jo, Sangwoo Ha, Sangyeob Kim, Hoi-Jun Yoo:
NoPIM: Functional Network-on-Chip Architecture for Scalable High-Density Processing-in-Memory-based Accelerator. COOL CHIPS 2024: 1-3 - [c31]Gwangtae Park, Seokchan Song, Haoyang Sang, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo:
A Low-power and Real-time Neural-Rendering Dense SLAM Processor with 3-Level Hierarchical Sparsity Exploitation. COOL CHIPS 2024: 1-3 - [c30]Junha Ryu, Hankyul Kwon, Wonhoon Park, Zhiyong Li, Beomseok Kwon, Donghyeon Han, Dongseok Im, Sangyeob Kim, Hyungnam Joo, Minsung Kim, Hoi-Jun Yoo:
A Low-Power Neural Graphics System for Instant 3D Modeling and Real-Time Rendering on Mobile AR/VR Devices. COOL CHIPS 2024: 1-3 - [c29]Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Hoi-Jun Yoo:
Two-Step Spike Encoding Scheme and Architecture for Highly Sparse Spiking-Neural-Network. ISCAS 2024: 1-5 - [c28]Sangyeob Kim, Sangjin Kim, Wooyoung Jo, Soyeon Kim, Seongyon Hong, Hoi-Jun Yoo:
20.5 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. ISSCC 2024: 368-370 - [c27]Junha Ryu, Hankyul Kwon, Wonhoon Park, Zhiyong Li, Beomseok Kwon, Donghyeon Han, Dongseok Im, Sangyeob Kim, Hyungnam Joo, Hoi-Jun Yoo:
20.7 NeuGPU: A 18.5mJ/Iter Neural-Graphics Processing Unit for Instant-Modeling and Real-Time Rendering with Segmented-Hashing Architecture. ISSCC 2024: 372-374 - [c26]Gwangtae Park, Seokchan Song, Haoyang Sang, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo:
20.8 Space-Mate: A 303.5mW Real-Time Sparse Mixture-of-Experts-Based NeRF-SLAM Processor for Mobile Spatial Computing. ISSCC 2024: 374-376 - 2023
- [j14]Sangyeob Kim, Hoi-Jun Yoo:
C-DNN V2: Complementary Deep-Neural-Network Processor With Full-Adder/OR-Based Reduction Tree and Reconfigurable Spatial Weight Reuse. IEEE J. Emerg. Sel. Topics Circuits Syst. 13(4): 1026-1039 (2023) - [j13]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) - [j12]Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Kwantae Kim, Hoi-Jun Yoo:
Neuro-CIM: ADC-Less Neuromorphic Computing-in-Memory Processor With Operation Gating/Stopping and Digital-Analog Networks. IEEE J. Solid State Circuits 58(10): 2931-2945 (2023) - [c25]Jiwon Choi, Sangyeob Kim, Wonhoon Park, Wooyoung Jo, Hoi-Jun Yoo:
A Resource-Efficient Super-Resolution FPGA Processor with Heterogeneous CNN and SNN Core Architecture. A-SSCC 2023: 1-3 - [c24]Soyeon Um, Sangjin Kim, Seongyon Hong, Sangyeob Kim, Hoi-Jun Yoo:
LOG-CIM: A 116.4 TOPS/W Digital Computing-In-Memory Processor Supporting a Wide Range of Logarithmic Quantization with Zero-Aware 6T Dual-WL Cell. A-SSCC 2023: 1-3 - [c23]Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, Jongjun Park, Hoi-Jun Yoo:
A Low-power Neural 3D Rendering Processor with Bio-inspired Visual Perception Core and Hybrid DNN Acceleration. COOL CHIPS 2023: 1-3 - [c22]Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Donghyeon Han, Jiwon Choi, Hoi-Jun Yoo:
COOL-NPU: Complementary Online Learning Neural Processing Unit with CNN-SNN Heterogeneous Core and Event-driven Backpropagation. COOL CHIPS 2023: 1-3 - [c21]Seongyon Hong, Soyeon Um, Sangjin Kim, Sangyeob Kim, Wooyoung Jo, Hoi-Jun Yoo:
A 332 TOPS/W Input/Weight-Parallel Computing-in-Memory Processor with Voltage-Capacitance-Ratio Cell and Time-Based ADC. ISCAS 2023: 1-5 - [c20]Seryeong Kim, Soyeon Kim, Soyeon Um, Sangjin Kim, Zhiyong Li, Sangyeob Kim, Wooyoung Jo, Hoi-Jun Yoo:
A Reconfigurable 1T1C eDRAM-based Spiking Neural Network Computing-In-Memory Processor for High System-Level Efficiency. ISCAS 2023: 1-5 - [c19]Donghyeon Han, Junha Ryu, Sangyeob Kim, Sangjin Kim, Hoi-Jun Yoo:
MetaVRain: A 133mW Real-Time Hyper-Realistic 3D-NeRF Processor with 1D-2D Hybrid-Neural Engines for Metaverse on Mobile Devices. ISSCC 2023: 50-51 - [c18]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 - [c17]Sangyeob Kim, Soyeon Kim, Seongyon Hong, Sangjin Kim, Donghyeon Han, Hoi-Jun Yoo:
C-DNN: A 24.5-85.8TOPS/W Complementary-Deep-Neural-Network Processor with Heterogeneous CNN/SNN Core Architecture and Forward-Gradient-Based Sparsity Generation. ISSCC 2023: 334-335 - [c16]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 - [c15]Seokchan Song, Donghyeon Han, Sangjin Kim, Sangyeob Kim, Gwangtae Park, Hoi-Jun Yoo:
GPPU: A 330.4-μJ/ task Neural Path Planning Processor with Hybrid GNN Acceleration for Autonomous 3D Navigation. VLSI Technology and Circuits 2023: 1-2 - [c14]Wenao Xie, Haoyang Sang, Beomseok Kwon, Dongseok Im, Sangjin Kim, Sangyeob Kim, Hoi-Jun Yoo:
A 709.3 TOPS/W Event-Driven Smart Vision SoC with High-Linearity and Reconfigurable MRAM PIM. VLSI Technology and Circuits 2023: 1-2 - 2022
- [j11]Kwantae Kim, Sangyeob Kim, Hoi-Jun Yoo:
Design of Sub-10-μW Sub-0.1% THD Sinusoidal Current Generator IC for Bio-Impedance Sensing. IEEE J. Solid State Circuits 57(2): 586-595 (2022) - [j10]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) - [j9]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) - [j8]Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Donghyeon Han, Wooyoung Jo, Hoi-Jun Yoo:
TSUNAMI: Triple Sparsity-Aware Ultra Energy-Efficient Neural Network Training Accelerator With Multi-Modal Iterative Pruning. IEEE Trans. Circuits Syst. I Regul. Pap. 69(4): 1494-1506 (2022) - [j7]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) - [c13]Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Kwantae Kim, Hoi-Jun Yoo:
Neuro-CIM: A 310.4 TOPS/W Neuromorphic Computing-in-Memory Processor with Low WL/BL activity and Digital-Analog Mixed-mode Neuron Firing. HCS 2022: 1-25 - [c12]Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Kwantae Kim, Hoi-Jun Yoo:
Neuro-CIM: A 310.4 TOPS/W Neuromorphic Computing-in-Memory Processor with Low WL/BL activity and Digital-Analog Mixed-mode Neuron Firing. VLSI Technology and Circuits 2022: 38-39 - [i2]Sangyeob Kim, Sangjin Kim, Soyeon Um, Soyeon Kim, Hoi-Jun Yoo:
Two-Step Spike Encoding Scheme and Architecture for Highly Sparse Spiking-Neural-Network. CoRR abs/2202.03601 (2022) - 2021
- [j6]Sanghoon Kang, Donghyeon Han, Juhyoung Lee, Dongseok Im, Sangyeob Kim, Soyeon Kim, Junha Ryu, Hoi-Jun Yoo:
GANPU: An Energy-Efficient Multi-DNN Training Processor for GANs With Speculative Dual-Sparsity Exploitation. IEEE J. Solid State Circuits 56(9): 2845-2857 (2021) - [j5]Soyeon Kim, Sanghoon Kang, Donghyeon Han, Sangjin Kim, Sangyeob Kim, Hoi-Jun Yoo:
An Energy-Efficient GAN Accelerator With On-Chip Training for Domain-Specific Optimization. IEEE J. Solid State Circuits 56(10): 2968-2980 (2021) - [j4]Soyeon Um, Sangyeob Kim, Sangjin Kim, Hoi-Jun Yoo:
A 43.1TOPS/W Energy-Efficient Absolute-Difference-Accumulation Operation Computing-In-Memory With Computation Reuse. IEEE Trans. Circuits Syst. II Express Briefs 68(5): 1605-1609 (2021) - [j3]Soyeon Kim, Sangjin Kim, Sangyeob Kim, Donghyeon Han, Hoi-Jun Yoo:
A 64.1mW Accurate Real-Time Visual Object Tracking Processor With Spatial Early Stopping on Siamese Network. IEEE Trans. Circuits Syst. II Express Briefs 68(5): 1675-1679 (2021) - [c11]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 - [c10]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 - [c9]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 - [c8]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 - [c7]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
- [j2]Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Jinsu Lee, Hoi-Jun Yoo:
A Power-Efficient CNN Accelerator With Similar Feature Skipping for Face Recognition in Mobile Devices. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. 67-I(4): 1181-1193 (2020) - [c6]Soyeon Kim, Sanghoon Kang, Donghyeon Han, Sangyeob Kim, Sangjin Kim, Hoi-Jun Yoo:
An Energy-Efficient GAN Accelerator with On-chip Training for Domain Specific Optimization. A-SSCC 2020: 1-4 - [c5]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 - [c4]Sanghoon Kang, Donghyeon Han, Juhyoung Lee, Dongseok Im, Sangyeob Kim, Soyeon Kim, Hoi-Jun Yoo:
7.4 GANPU: A 135TFLOPS/W Multi-DNN Training Processor for GANs with Speculative Dual-Sparsity Exploitation. ISSCC 2020: 140-142 - [c3]Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Jinmook Lee, Hoi-Jun Yoo:
A 146.52 TOPS/W Deep-Neural-Network Learning Processor with Stochastic Coarse-Fine Pruning and Adaptive Input/Output/Weight Skipping. VLSI Circuits 2020: 1-2
2010 – 2019
- 2019
- [j1]Jinmook Lee, Changhyeon Kim, Sanghoon Kang, Dongjoo Shin, Sangyeob Kim, Hoi-Jun Yoo:
UNPU: An Energy-Efficient Deep Neural Network Accelerator With Fully Variable Weight Bit Precision. IEEE J. Solid State Circuits 54(1): 173-185 (2019) - [c2]Sangyeob Kim, Juhyoung Lee, Sanghoon Kang, Jinsu Lee, Hoi-Jun Yoo:
A 15.2 TOPS/W CNN Accelerator with Similar Feature Skipping for Face Recognition in Mobile Devices. ISCAS 2019: 1-5 - 2018
- [c1]Jinmook Lee, Changhyeon Kim, Sanghoon Kang, Dongjoo Shin, Sangyeob Kim, Hoi-Jun Yoo:
UNPU: A 50.6TOPS/W unified deep neural network accelerator with 1b-to-16b fully-variable weight bit-precision. ISSCC 2018: 218-220
Coauthor Index
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last updated on 2024-08-05 21:24 CEST by the dblp team
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