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2020 – today
- 2024
[c25]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- [c24]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 - [c23]Junha Ryu, Hankyul Kwon, Wonhoon Park, Zhiyong Li, Beomseok Kwon, Donghyeon Han, Dongseok Im, Sangyeob Kim, Hyungnam Joo, Minsung Kim, Hoi-Jun Yoo:
NeuGPU: A Neural Graphics Processing Unit for Instant Modeling and Real-Time Rendering on Mobile AR/VR Devices. HCS 2024: 1 - [c22]Seokchan Song, Haoyang Sang, Dongseok Im, Donghyeon Han, Sangyeob Kim, Hongseok Lee, Hoi-Jun Yoo:
Space-Mate: A 303.5mW Real-Time NeRF SLAM Processor with Sparse-Mixture-of-Experts-based Acceleration. HCS 2024: 1 - [c21]Dongseok Im, Hoi-Jun Yoo:
LUTein: Dense-Sparse Bit-Slice Architecture With Radix-4 LUT-Based Slice-Tensor Processing Units. HPCA 2024: 747-759 - [c20]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 - [c19]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
- [j10]Dongseok Im, Gwangtae Park, Junha Ryu, Zhiyong Li, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, Hoi-Jun Yoo:
DSPU: An Efficient Deep Learning-Based Dense RGB-D Data Acquisition With Sensor Fusion and 3-D Perception SoC. IEEE J. Solid State Circuits 58(1): 177-188 (2023) - [j9]Zhiyong Li, Sangjin Kim, Dongseok Im, Donghyeon Han, Hoi-Jun Yoo:
An Efficient Deep-Learning-Based Super-Resolution Accelerating SoC With Heterogeneous Accelerating and Hierarchical Cache. IEEE J. Solid State Circuits 58(3): 614-623 (2023) - [j8]Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, Hoi-Jun Yoo:
A Mobile 3-D Object Recognition Processor With Deep-Learning-Based Monocular Depth Estimation. IEEE Micro 43(3): 74-82 (2023) - [c18]Jongjun Park, Donghyeon Han, Junha Ryu, Dongseok Im, Gwangtae Park, Hoi-Jun Yoo:
A 33.6 FPS Embedding based Real-time Neural Rendering Accelerator with Switchable Computation Skipping Architecture on Edge Device. A-SSCC 2023: 1-3 - [c17]Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Hoi-Jun Yoo:
Sibia: Signed Bit-slice Architecture for Dense DNN Acceleration with Slice-level Sparsity Exploitation. HPCA 2023: 69-80 - [c16]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
- [j7]Dongseok Im, Donghyeon Han, Sanghoon Kang, Hoi-Jun Yoo:
A Pipelined Point Cloud Based Neural Network Processor for 3-D Vision With Large-Scale Max Pooling Layer Prediction. IEEE J. Solid State Circuits 57(2): 661-670 (2022) - [j6]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
A Mobile DNN Training Processor With Automatic Bit Precision Search and Fine-Grained Sparsity Exploitation. IEEE Micro 42(2): 16-25 (2022) - [c15]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
A 0.95 mJ/frame DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation. AICAS 2022: 37-40 - [c14]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
A DNN Training Processor for Robust Object Detection with Real-World Environmental Adaptation. AICAS 2022: 501 - [c13]Zhiyong Li, Sangjin Kim, Dongseok Im, Donghyeon Han, Hoi-Jun Yoo:
An 0.92 mJ/frame High-quality FHD Super-resolution Mobile Accelerator SoC with Hybrid-precision and Energy-efficient Cache. CICC 2022: 1-2 - [c12]Dongseok Im, Gwangtae Park, Junha Ryu, Zhiyong Li, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, Hoi-Jun Yoo:
A Low-power and Real-time 3D Object Recognition Processor with Dense RGB-D Data Acquisition in Mobile Platforms. COOL CHIPS 2022: 1-3 - [c11]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
HNPU-V2: A 46.6 FPS DNN Training Processor for Real-World Environmental Adaptation based Robust Object Detection on Mobile Devices. HCS 2022: 1-18 - [c10]Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Wonhoon Park, Hankyul Kwon, Hoi-Jun Yoo:
DSPU: A 281.6mW Real-Time Deep Learning-Based Dense RGB-D Data Acquisition with Sensor Fusion and 3D Perception System-on-Chip. HCS 2022: 1-25 - [c9]Zhiyong Li, Sangjin Kim, Dongseok Im, Donghyeon Han, Hoi-Jun Yoo:
An Efficient High-quality FHD Super-resolution Mobile Accelerator SoC with Hybrid-precision and Energy-efficient Cache. HCS 2022: 1-26 - [c8]Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Sanghoon Kang, Donghyeon Han, Jinsu Lee, Hoi-Jun Yoo:
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. ISSCC 2022: 510-512 - [i1]Dongseok Im, Gwangtae Park, Zhiyong Li, Junha Ryu, Hoi-Jun Yoo:
Energy-efficient Dense DNN Acceleration with Signed Bit-slice Architecture. CoRR abs/2203.07679 (2022) - 2021
- [j5]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) - [j4]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
HNPU: An Adaptive DNN Training Processor Utilizing Stochastic Dynamic Fixed-Point and Active Bit-Precision Searching. IEEE J. Solid State Circuits 56(9): 2858-2869 (2021) - [j3]Junha Ryu, Gwangtae Park, Dongseok Im, Ji-Hoon Kim, Hoi-Jun Yoo:
A 0.82 μW CIS-Based Action Recognition SoC With Self-Adjustable Frame Resolution for Always-on IoT Devices. IEEE Trans. Circuits Syst. II Express Briefs 68(5): 1700-1704 (2021) - [c7]Donghyeon Han, Dongseok Im, Gwangtae Park, Youngwoo Kim, Seokchan Song, Juhyoung Lee, Hoi-Jun Yoo:
An Energy-Efficient Deep Neural Network Training Processor with Bit-Slice-Level Reconfigurability and Sparsity Exploitation. COOL CHIPS 2021: 1-3 - [c6]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 - [c5]Zhiyong Li, Dongseok Im, Jinsu Lee, Hoi-Jun Yoo:
A 3.6 TOPS/W Hybrid FP-FXP Deep Learning Processor with Outlier Compensation for Image-to-Image Application. ISCAS 2021: 1-5 - [c4]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 - 2020
- [j2]Gwangtae Park, Dongseok Im, Donghyeon Han, Hoi-Jun Yoo:
A 1.15 TOPS/W Energy-Efficient Capsule Network Accelerator for Real-Time 3D Point Cloud Segmentation in Mobile Environment. IEEE Trans. Circuits Syst. II Express Briefs 67-II(9): 1594-1598 (2020) - [j1]Dongseok Im, Donghyeon Han, Sungpill Choi, Sanghoon Kang, Hoi-Jun Yoo:
DT-CNN: An Energy-Efficient Dilated and Transposed Convolutional Neural Network Processor for Region of Interest Based Image Segmentation. IEEE Trans. Circuits Syst. 67-I(10): 3471-3483 (2020) - [c3]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 - [c2]Dongseok Im, Sanghoon Kang, Donghyeon Han, Sungpill Choi, Hoi-Jun Yoo:
A 4.45 ms Low-Latency 3D Point-Cloud-Based Neural Network Processor for Hand Pose Estimation in Immersive Wearable Devices. VLSI Circuits 2020: 1-2
2010 – 2019
- 2019
- [c1]Dongseok Im, Donghyeon Han, Sungpill Choi, Sanghoon Kang, Hoi-Jun Yoo:
DT-CNN: Dilated and Transposed Convolution Neural Network Accelerator for Real-Time Image Segmentation on Mobile Devices. ISCAS 2019: 1-5
Coauthor Index
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