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2020 – today
- 2024
[c12]Minsang Yu, Minuk Hong, Sugil Lee, Seungsu Kim, Jongeun Lee:
PyAIM: Pynq-Based Scalable Analog In-Memory Computing Prototyping Platform. AICAS 2024: 174-178- 2023
- [j5]Sugil Lee
, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi:
Offline Training-Based Mitigation of IR Drop for ReRAM-Based Deep Neural Network Accelerators. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(2): 521-532 (2023) - [j4]Chenghao Quan, Mohammed E. Fouda, Sugil Lee, Giju Jung, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi:
Training-Free Stuck-At Fault Mitigation for ReRAM-Based Deep Learning Accelerators. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(7): 2174-2186 (2023) - [c11]Jaewoo Park, Sugil Lee, Jongeun Lee:
NTT-PIM: Row-Centric Architecture and Mapping for Efficient Number-Theoretic Transform on PIM. DAC 2023: 1-6 - [i1]Jaewoo Park, Sugil Lee, Jongeun Lee:
NTT-PIM: Row-Centric Architecture and Mapping for Efficient Number-Theoretic Transform on PIM. CoRR abs/2310.09715 (2023) - 2022
- [j3]Jooyeon Choi, Hyeonuk Sim, Sangyun Oh, Sugil Lee, Jongeun Lee:
MLogNet: A Logarithmic Quantization-Based Accelerator for Depthwise Separable Convolution. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(12): 5220-5231 (2022) - [c10]Chenghao Quan, Mohammed E. Fouda, Sugil Lee, Jongeun Lee:
Multi-Fidelity Nonideality Simulation and Evaluation Framework for Resistive Neuromorphic Computing. IEEECONF 2022: 1152-1156 - [c9]Sugil Lee, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi:
Accurate Prediction of ReRAM Crossbar Performance Under I-V Nonlinearity and IR Drop. ICCD 2022: 9-16 - 2021
- [c8]Sangyun Oh, Hyeonuk Sim, Sugil Lee, Jongeun Lee:
Automated Log-Scale Quantization for Low-Cost Deep Neural Networks. CVPR 2021: 742-751 - [c7]Giju Jung, Mohammed E. Fouda, Sugil Lee, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi:
Cost- and Dataset-free Stuck-at Fault Mitigation for ReRAM-based Deep Learning Accelerators. DATE 2021: 1733-1738 - [c6]Sugil Lee, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi:
Fast and Low-Cost Mitigation of ReRAM Variability for Deep Learning Applications. ICCD 2021: 269-276 - 2020
- [j2]Mohammed E. Fouda, Sugil Lee, Jongeun Lee, Gun Hwan Kim, Fadi J. Kurdahi, Ahmed M. Eltawil:
IR-QNN Framework: An IR Drop-Aware Offline Training of Quantized Crossbar Arrays. IEEE Access 8: 228392-228408 (2020) - [c5]Sugil Lee, Giju Jung, Mohammed E. Fouda, Jongeun Lee, Ahmed M. Eltawil, Fadi J. Kurdahi:
Learning to Predict IR Drop with Effective Training for ReRAM-based Neural Network Hardware. DAC 2020: 1-6 - [c4]Segi Lee, Sugil Lee, Jongeun Lee, Jong-Moon Choi, Do-Wan Kwon, Seung-Kwang Hong, Kee-Won Kwon:
Architecture-Accuracy Co-optimization of ReRAM-based Low-cost Neural Network Processor. ACM Great Lakes Symposium on VLSI 2020: 427-432
2010 – 2019
- 2019
- [j1]Sugil Lee, Daewoo Kim, Dong Nguyen, Jongeun Lee:
Double MAC on a DSP: Boosting the Performance of Convolutional Neural Networks on FPGAs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(5): 888-897 (2019) - [c3]Daewoo Kim, Sugil Lee, Jongeun Lee:
On-chip memory optimization for high-level synthesis of multi-dimensional data on FPGA. ASP-DAC 2019: 243-248 - [c2]Sugil Lee, Hyeon Uk Sim, Jooyeon Choi, Jongeun Lee:
Successive Log Quantization for Cost-Efficient Neural Networks Using Stochastic Computing. DAC 2019: 7 - 2018
- [c1]Aidyn Zhakatayev, Sugil Lee, Hyeon Uk Sim, Jongeun Lee:
Sign-magnitude SC: getting 10X accuracy for free in stochastic computing for deep neural networks. DAC 2018: 158:1-158:6
Coauthor Index
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