| International Journal Papers |
| Myeonggu Kang, Junyoung Park, Jaekang Shin, Jaekang Shin, Lee-Sup Kim |
| ToEx: Accelerating Generation Stage of Transformer-based Language Models via Token-adaptive Early Exit |
| IEEE Transactions on Computers, 2024 |
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| Myeonggu Kang, Hyein Shin, Junkyum Kim, Lee-Sup Kim |
| MGen: A Framework for Energy-Efficient In-ReRAM Acceleration of Multi-Task BERT |
| IEEE Transactions on Computers, 2023 |
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| Hyein Shin, Myeonggu Kang, Lee-Sup Kim |
| Fault-free: A Framework for Analysis and Mitigation of Stuck-At-Fault on Realistic ReRAM-based DNN Accelerators |
| IEEE Transactions on Computers, 2023 |
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| Myeonggu Kang, Hyein Shin, Lee-Sup Kim |
| A Framework for Accelerating Transformer-based Language Model on ReRAM-based Architecture |
| IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022 |
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| Myeonggu Kang, Hyeonuk Kim, Hyein Shin, Jaehyeong Sim, Kyeonghan Kim, Lee-Sup Kim |
| S-FLASH: A NAND Flash-based Deep Neural Network Accelerator Exploiting Bit-level Sparsity |
| IEEE Transactions on Computers, 2022 |
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| Seungkyu Choi, Jaehyeong Sim, Myeonggu Kang, Yeongjae Choi, Hyeonuk Kim, Lee-Sup Kim |
| An Energy-Efficient Deep Convolutional Neural Network Training Accelerator for In-Situ Personalization on Smart Devices |
| IEEE Journal of Solid-State Circuits, 2020 |
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| International Conference Papers |
| Junyoung Park, Myeonggu Kang, Yunki Han, Yanggon Kim, Jaekang Shin, Lee-Sup Kim |
| Token-Picker: Accelerating Attention in Text Generation with Minimized Memory Transfer via Probability Estimation (Best Paper Award) |
| IEEE/ACM Design Automation Conference, 2024 |
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| Junkyum Kim, Myeonggu Kang, Yunki Han, Yanggon Kim, Lee-Sup Kim |
| OptimStore: In-Storage Optimization of Large Scale DNNs with On-Die Processing |
| IEEE International Symposium on High-Performance Computer Architecture, 2023 |
| |
| Hyein Shin, Myeonggu Kang, Lee-Sup Kim |
| Re2fresh: A Framework for Mitigating Read Disturbance in ReRAM-based DNN Accelerators |
| IEEE/ACM International Conference On Computer Aided Design, 2022 |
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| Hancheon Yun, Hyein Shin, Myeonggu Kang, Lee-Sup Kim |
| Optimizing ADC Utilization through Value-Aware Bypass in ReRAM-based DNN Accelerator |
| IEEE/ACM Design Automation Conference, 2021 |
| |
| Hyein Shin, Myeonggu Kang, Lee-Sup Kim |
| Fault-free: A Fault-resilient Deep Neural Network Accelerator based on Realistic ReRAM Devices |
| IEEE/ACM Design Automation Conference, 2021 |
| |
| Myeonggu Kang, Hyein Shin, Jaekang Shin, Lee-Sup Kim |
| A Framework for Area-efficient Multi-task BERT Execution on ReRAM-based Accelerators |
| IEEE/ACM International Conference On Computer Aided Design, 2021 |
| |
| Hyein Shin, Myeonggu Kang, Lee-Sup Kim |
| Thermal-aware Optimization Framework for ReRAM-based Deep Neural Network Acceleration |
| IEEE/ACM International Conference On Computer Aided Design, 2020 |
| |
| Kyeonghan Kim, Hyein Shin, Jaehyeong Sim, Myeonggu Kang, Lee-Sup Kim |
| An Energy-efficient Processing-in-memory Architecture for Long Short Term Memory in Spin Orbit Torque MRAM |
| IEEE/ACM International Conference On Computer Aided Design, 2019 |
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| Seungkyu Choi, Jaehyeong Sim, Myeonggu Kang, Yeongjae Choi, Hyeonuk Kim, Lee-Sup Kim |
| A 47.4uJ/epoch Trainable Deep Convolutional Neural Network Accelerator for In-Situ Personalization on Smart Devices |
| IEEE Asian Solid-State Circuits Conference, 2019 |
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| Seungkyu Choi, Jaehyeong Sim, Myeonggu Kang, Lee-Sup Kim |
| TrainWare: A Memory Optimized Weight Update Architecture for On-Device Convolutional Neural Network Training |
| ACM/IEEE International Symposium on Low Power Electronics and Design, 2018 |
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