Sugil Lee

20 papers A* 5A 2C 2Journal 7Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Mitigating the Impact of ReRAM I-V Nonlinearity and IR Drop via Fast Offline Network Training.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Sugil Lee, Mohammed E. Fouda, Chenghao Quan, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi
2024 A conf
FlexInt: A New Number Format for Robust Sub-8-Bit Neural Network Inference.
ICCAD
Minuk Hong, Hyeonuk Sim, Sugil Lee, Jongeun Lee
2024 — conf
PyAIM: Pynq-Based Scalable Analog In-Memory Computing Prototyping Platform.
AICAS
Minsang Yu, Minuk Hong, Sugil Lee, Seungsu Kim, Jongeun Lee
2023 A* conf
NTT-PIM: Row-Centric Architecture and Mapping for Efficient Number-Theoretic Transform on PIM.
DAC
Jaewoo Park, Sugil Lee, Jongeun Lee
2023 J jnl
NTT-PIM: Row-Centric Architecture and Mapping for Efficient Number-Theoretic Transform on PIM.
CoRR
Jaewoo Park, Sugil Lee, Jongeun Lee
2023 J jnl
Offline Training-Based Mitigation of IR Drop for ReRAM-Based Deep Neural Network Accelerators.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Sugil Lee, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi
2023 J jnl
Training-Free Stuck-At Fault Mitigation for ReRAM-Based Deep Learning Accelerators.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Chenghao Quan, Mohammed E. Fouda, Sugil Lee, Giju Jung, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi
2022 C conf
Accurate Prediction of ReRAM Crossbar Performance Under I-V Nonlinearity and IR Drop.
ICCD
Sugil Lee, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi
2022 J jnl
MLogNet: A Logarithmic Quantization-Based Accelerator for Depthwise Separable Convolution.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Jooyeon Choi, Hyeonuk Sim, Sangyun Oh, Sugil Lee, Jongeun Lee
2022 — conf
Multi-Fidelity Nonideality Simulation and Evaluation Framework for Resistive Neuromorphic Computing.
IEEECONF
Chenghao Quan, Mohammed E. Fouda, Sugil Lee, Jongeun Lee
2021 A* conf
Automated Log-Scale Quantization for Low-Cost Deep Neural Networks.
CVPR
Sangyun Oh, Hyeonuk Sim, Sugil Lee, Jongeun Lee
2021 A conf
Cost- and Dataset-free Stuck-at Fault Mitigation for ReRAM-based Deep Learning Accelerators.
DATE
Giju Jung, Mohammed E. Fouda, Sugil Lee, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi
2021 C conf
Fast and Low-Cost Mitigation of ReRAM Variability for Deep Learning Applications.
ICCD
Sugil Lee, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi
2020 — conf
Architecture-Accuracy Co-optimization of ReRAM-based Low-cost Neural Network Processor.
ACM Great Lakes Symposium on VLSI
Segi Lee, Sugil Lee, Jongeun Lee, Jong-Moon Choi, Do-Wan Kwon, Seung-Kwang Hong, Kee-Won Kwon
2020 J jnl
IR-QNN Framework: An IR Drop-Aware Offline Training of Quantized Crossbar Arrays.
IEEE Access
Mohammed E. Fouda, Sugil Lee, Jongeun Lee, Gun Hwan Kim, Fadi J. Kurdahi, Ahmed M. Eltawil
2020 A* conf
Learning to Predict IR Drop with Effective Training for ReRAM-based Neural Network Hardware.
DAC
Sugil Lee, Giju Jung, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi
2019 J jnl
Double MAC on a DSP: Boosting the Performance of Convolutional Neural Networks on FPGAs.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Sugil Lee, Daewoo Kim, Dong Nguyen, Jongeun Lee
2019 — conf
On-chip memory optimization for high-level synthesis of multi-dimensional data on FPGA.
ASP-DAC
Daewoo Kim, Sugil Lee, Jongeun Lee
2019 A* conf
Successive Log Quantization for Cost-Efficient Neural Networks Using Stochastic Computing.
DAC
Sugil Lee, Hyeon Uk Sim, Jooyeon Choi, Jongeun Lee
2018 A* conf
Sign-magnitude SC: getting 10X accuracy for free in stochastic computing for deep neural networks.
DAC
Aidyn Zhakatayev, Sugil Lee, Hyeon Uk Sim, Jongeun Lee