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Showing results 1 to 9 of 9

1
A 47.4µJ/epoch Trainable Deep Convolutional Neural Network Accelerator for In-Situ Personalization on Smart Devices

Choi, Seungkyu; Sim, Jaehyeong; Kang, Myeonggu; Choi, Yeongjae; Kim, Hyeonuk; Kim, Lee-Sup, 2019 IEEE Asian Solid-State Circuits Conference, IEEE/SSCS, 2019-11-05

2
A Framework for Area-efficient Multi-task BERT Execution on ReRAM-based Accelerators

Kang, Myeonggu; Shin, Hyein; Shin, Jaekang; Kim, Lee-Sup, 40th IEEE/ACM International Conference on Computer Aided Design (ICCAD), IEEE/ACM, 2021-11

3
A Thermal-aware Optimization Framework for ReRAM-based Deep Neural Network Acceleration

Shin, Hyein; Kang, Myeonggu; Kim, Lee-Sup, 39th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2020, IEEE/ACM, 2020-11

4
An Energy-efficient Processing-in-memory Architecture for Long Short Term Memory in Spin Orbit Torque MRAM

Kim, Kyeonghan; Shin, Hyein; Sim, Jaehyeong; Kang, Myeonggu; Kim, Lee-Sup, 38th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2019, IEEE/ACM, 2019-11-06

5
Fault-free: A Fault-resilient Deep Neural Network Accelerator based on Realistic ReRAM Devices

Shin, Hyein; Kang, Myeonggu; Kim, Lee-Sup, 58th ACM/IEEE Design Automation Conference, DAC 2021, Institute of Electrical and Electronics Engineers Inc., 2021-12

6
Optimizing ADC Utilization through Value-Aware Bypass in ReRAM-based DNN Accelerator

Yun, HanCheon; Shin, Hyein; Kang, Myeonggu; Kim, Lee-Sup, 58th ACM/IEEE Design Automation Conference, DAC 2021, Institute of Electrical and Electronics Engineers Inc., 2021-12

7
OptimStore: In-Storage Optimization of Large Scale DNNs with On-Die Processing

Kim, Junkyum; Kang, Myeonggu; Han, Yunki; Kim, Yang-Gon; Kim, Lee-Sup, 29th IEEE International Symposium on High-Performance Computer Architecture, HPCA 2023, pp.611 - 623, IEEE Computer Society, 2023-02-28

8
Re(2)fresh: A Framework for Mitigating Read Disturbance in ReRAM-based DNN Accelerators

Shin, Hyein; Kang, Myeonggu; Kim, Lee-Sup, 41st IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2022, IEEE/ACM, 2022-11

9
TrainWare: A Memory Optimized Weight Update Architecture for On-Device Convolutional Neural Network Training

Choi, Seungkyu; Sim, Jaehyeong; Kang, Myeonggu; Kim, Lee-Sup, 23rd IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), pp.104 - 109, ACM/IEEE, 2018-07-24

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