Jaeha Kung

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 44

Top Venues

CoRR

ISLPED

DATE

IEEE Comput. Archit. Lett.

Georgia Institute of Technology, Atlanta, GA, USA (PHD)

Education History

Georgia Institute of Technology, Atlanta, GA, USA

PHD

Publications

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)
Jooyeon Lee, Donghun Lee, Jaeha Kung
A Ready-to-Use RTL Generator for Systolic Tensor Arrays and Analysis Using Open-Source EDA Tools. ISCAS (2024)
Sangwoo Hwang, Jaeha Kung
One-Spike SNN: Single-Spike Phase Coding with Base Manipulation for ANN-to-SNN Conversion Loss Minimization. CoRR (2024)
Jungwoo Kim, Seonggyun Oh, Jaeha Kung, Yeseong Kim, Sungjin Lee
NDPipe: Exploiting Near-data Processing for Scalable Inference and Continuous Training in Photo Storage. ASPLOS (3) (2024)
Seonghun Jeong, Jooyeon Lee, Jaeha Kung
A Full SW-HW Demonstration of GEMM Accelerators with RISC-V Instruction Extensions. ICEIC (2024)
Taeryoung Seol, Sehwan Lee, Geunha Kim, Samhwan Kim, Euiseong Kim, Seungyeob Baik, Jaeha Kung, Ji-Woong Choi, Arup K. George, Junghyup Lee
A 1V 136.6dB-DR 4kHz-BW $\Delta\Sigma$ Current-to-Digital Converter with a Truncation-Noise-Shaped Baseline-Servo-Loop in 0.18\mu\mathrm{m}$ CMOS. ISSCC (2023)
Seock-Hwan Noh, Seungpyo Lee, Banseok Shin, Sehun Park, Yongjoo Jang, Jaeha Kung
All-rounder: A flexible DNN accelerator with diverse data format support. CoRR (2023)
Banseok Shin, Sehun Park, Jaeha Kung
Improving Hardware Efficiency of a Sparse Training Accelerator by Restructuring a Reduction Network. NEWCAS (2023)
Seock-Hwan Noh, Jahyun Koo, Seunghyun Lee, Jongse Park, Jaeha Kung
FlexBlock: A Flexible DNN Training Accelerator With Multi-Mode Block Floating Point Support. IEEE Trans. Computers 72 (9) (2023)
Gunho Park, Jaeha Kung, Youngjoo Lee
Simplified Compressor and Encoder Designs for Low-Cost Approximate Radix-4 Booth Multiplier. IEEE Trans. Circuits Syst. II Express Briefs 70 (3) (2023)
Seunghyun Lee, Jeik Choi, Seock-Hwan Noh, Jahyun Koo, Jaeha Kung
DBPS: Dynamic Block Size and Precision Scaling for Efficient DNN Training Supported by RISC-V ISA Extensions. DAC (2023)
Arup K. George, Wooyoon Shim, Jaeha Kung, Ji-Hoon Kim, Minkyu Je, Junghyup Lee
A 46-nF/10-MΩ Range 114-aF/0.37-Ω Resolution Parasitic- and Temperature-Insensitive Reconfigurable RC-to-Digital Converter in 0.18-μm CMOS. IEEE Trans. Circuits Syst. I Regul. Pap. 69 (3) (2022)
Seock-Hwan Noh, Junsang Park, Dahoon Park, Jahyun Koo, Jeik Choi, Jaeha Kung
LightNorm: Area and Energy-Efficient Batch Normalization Hardware for On-Device DNN Training. CoRR (2022)
Jooyeon Lee, Junsang Park, Seunghyun Lee, Jaeha Kung
Implication of Optimizing NPU Dataflows on Neural Architecture Search for Mobile Devices. ACM Trans. Design Autom. Electr. Syst. 27 (5) (2022)
Sejin Kim, Jungwoo Kim, Yongjoo Jang, Jaeha Kung, Sungjin Lee
SEMS: Scalable Embedding Memory System for Accelerating Embedding-Based DNNs. IEEE Comput. Archit. Lett. 21 (2) (2022)
Seock-Hwan Noh, Jahyun Koo, Seunghyun Lee, Jongse Park, Jaeha Kung
FlexBlock: A Flexible DNN Training Accelerator with Multi-Mode Block Floating Point Support. CoRR (2022)
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)
Sehun Park, Jae-Joon Kim, Jaeha Kung
AutoRelax: HW-SW Co-Optimization for Efficient SpGEMM Operations With Automated Relaxation in Deep Learning. IEEE Trans. Emerg. Top. Comput. 10 (3) (2022)
Seock-Hwan Noh, Junsang Park, Dahoon Park, Jahyun Koo, Jeik Choi, Jaeha Kung
LightNorm: Area and Energy-Efficient Batch Normalization Hardware for On-Device DNN Training. ICCD (2022)
Dahoon Park, Kon-Woo Kwon, Sunghoon Im, Jaeha Kung
ZeBRA: Precisely Destroying Neural Networks with Zero-Data Based Repeated Bit Flip Attack. BMVC (2021)
Sangwoo Hwang, Junghyup Lee, Jaeha Kung
Adaptive Input-to-Neuron Interlink Development in Training of Spike-Based Liquid State Machines. ISCAS (2021)
Naebeom Park, Sungju Ryu, Jaeha Kung, Jae-Joon Kim
High-throughput Near-Memory Processing on CNNs with 3D HBM-like Memory. ACM Trans. Design Autom. Electr. Syst. 26 (6) (2021)
Gunho Park, Jaeha Kung, Youngjoo Lee
Design and Analysis of Approximate Compressors for Balanced Error Accumulation in MAC Operator. IEEE Trans. Circuits Syst. I Regul. Pap. 68 (7) (2021)
Dahoon Park, Kon-Woo Kwon, Sunghoon Im, Jaeha Kung
ZeBRA: Precisely Destroying Neural Networks with Zero-Data Based Repeated Bit Flip Attack. CoRR (2021)
Yongjoo Jang, Sejin Kim, Daehoon Kim, Sungjin Lee, Jaeha Kung
Deep Partitioned Training From Near-Storage Computing to DNN Accelerators. IEEE Comput. Archit. Lett. 20 (1) (2021)
Minwoo Jang, Seungkyu Lee, Jaeha Kung, Daehoon Kim
Defending Against Flush+Reload Attack With DRAM Cache by Bypassing Shared SRAM Cache. IEEE Access 8 (2020)
Minsub Kim, Jaeha Kung, Sungjin Lee
Towards Scalable Analytics with Inference-Enabled Solid-State Drives. IEEE Comput. Archit. Lett. 19 (1) (2020)
Junki Park, Wooseok Yi, Daehyun Ahn, Jaeha Kung, Jae-Joon Kim
Balancing Computation Loads and Optimizing Input Vector Loading in LSTM Accelerators. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39 (9) (2020)
Junseo Jo, Jaeha Kung, Sunggu Lee, Youngjoo Lee
Similarity-Based LSTM Architecture for Energy-Efficient Edge-Level Speech Recognition. ISLPED (2019)
Sangwoo Jung, Seungsik Moon, Youngjoo Lee, Jaeha Kung
WMixNet: An Energy-Scalable and Computationally Lightweight Deep Learning Accelerator. ISLPED (2019)
Sangwoo Jung, Jaeha Kung
Noise Tolerance of an Energy-Scalable Deep Learning Model with Two Extreme Bit-Precisions. ISOCC (2019)
Jaeha Kung, Junki Park, Sehun Park, Jae-Joon Kim
Peregrine: A Flexible Hardware Accelerator for LSTM with Limited Synaptic Connection Patterns. DAC (2019)
Junki Park, Jaeha Kung, Wooseok Yi, Jae-Joon Kim
Maximizing system performance by balancing computation loads in LSTM accelerators. DATE (2018)
Jaeha Kung, Duckhwan Kim, Saibal Mukhopadhyay
Adaptive Precision Cellular Nonlinear Network. IEEE Trans. Very Large Scale Integr. Syst. 26 (5) (2018)
Saibal Mukhopadhyay, Marilyn Wolf, Mohammed Faisal Amir, Evan Gebhardt, Jong Hwan Ko, Jaeha Kung, Burhan Ahmad Musassar
The CAMEL approach to stacked sensor smart cameras. DATE (2018)
Jaeha Kung, David C. Zhang, Gooitzen S. van der Wal, Sek M. Chai, Saibal Mukhopadhyay
Efficient Object Detection Using Embedded Binarized Neural Networks. J. Signal Process. Syst. 90 (6) (2018)
Duckhwan Kim, Jaeha Kung, Saibal Mukhopadhyay
A Power-Aware Digital Multilayer Perceptron Accelerator with On-Chip Training Based on Approximate Computing. IEEE Trans. Emerg. Top. Comput. 5 (2) (2017)
Jaeha Kung, Yun Long, Duckhwan Kim, Saibal Mukhopadhyay
A Programmable Hardware Accelerator for Simulating Dynamical Systems. ISCA (2017)
Jong Hwan Ko, Duckhwan Kim, Taesik Na, Jaeha Kung, Saibal Mukhopadhyay
Adaptive weight compression for memory-efficient neural networks. DATE (2017)
Jong Hwan Ko, Yun Long, Mohammad Faisal Amir, Duckhwan Kim, Jaeha Kung, Taesik Na, Amit Ranjan Trivedi, Saibal Mukhopadhyay
Energy-efficient neural image processing for Internet-of-Things edge devices. MWSCAS (2017)
Taesik Na, Jong Hwan Ko, Jaeha Kung, Saibal Mukhopadhyay
On-chip training of recurrent neural networks with limited numerical precision. IJCNN (2017)
Yun Long, Eui Min Jung, Jaeha Kung, Saibal Mukhopadhyay
ReRAM Crossbar based Recurrent Neural Network for human activity detection. IJCNN (2016)
Jaeha Kung, Duckhwan Kim, Saibal Mukhopadhyay
Dynamic Approximation with Feedback Control for Energy-Efficient Recurrent Neural Network Hardware. ISLPED (2016)
Duckhwan Kim, Jaeha Kung, Sek M. Chai, Sudhakar Yalamanchili, Saibal Mukhopadhyay
Neurocube: A Programmable Digital Neuromorphic Architecture with High-Density 3D Memory. ISCA (2016)
Jaeha Kung, Duckhwan Kim, Saibal Mukhopadhyay
On the Impact of Energy-Accuracy Tradeoff in a Digital Cellular Neural Network for Image Processing. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 34 (7) (2015)
Jaeha Kung, Duckhwan Kim, Saibal Mukhopadhyay
A power-aware digital feedforward neural network platform with backpropagation driven approximate synapses. ISLPED (2015)
Jaeha Kung, Youngsoo Shin
Compact thermal models: Assessment and pitfalls. ISOCC (2011)
Jaeha Kung, Inhak Han, Sachin S. Sapatnekar, Youngsoo Shin
Thermal signature: a simple yet accurate thermal index for floorplan optimization. DAC (2011)

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Publication Activity (10 Years)

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Jaeha Kung