Sugil Lee

Orcid: 0000-0003-3092-6501

According to our database¹, Sugil Lee authored at least 17 papers between 2018 and 2024.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

PyAIM: Pynq-Based Scalable Analog In-Memory Computing Prototyping Platform.

[BibT_eX]

[DOI]

Proceedings of the 6th IEEE International Conference on AI Circuits and Systems, 2024

2023

Training-Free Stuck-At Fault Mitigation for ReRAM-Based Deep Learning Accelerators.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., July, 2023

Offline Training-Based Mitigation of IR Drop for ReRAM-Based Deep Neural Network Accelerators.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2023

NTT-PIM: Row-Centric Architecture and Mapping for Efficient Number-Theoretic Transform on PIM.

[BibT_eX]

[DOI]

Jaewoo Park

Sugil Lee

Jongeun Lee

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

MLogNet: A Logarithmic Quantization-Based Accelerator for Depthwise Separable Convolution.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

Accurate Prediction of ReRAM Crossbar Performance Under I-V Nonlinearity and IR Drop.

[BibT_eX]

[DOI]

Proceedings of the IEEE 40th International Conference on Computer Design, 2022

Multi-Fidelity Nonideality Simulation and Evaluation Framework for Resistive Neuromorphic Computing.

[BibT_eX]

[DOI]

Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021

Fast and Low-Cost Mitigation of ReRAM Variability for Deep Learning Applications.

[BibT_eX]

[DOI]

Proceedings of the 39th IEEE International Conference on Computer Design, 2021

Cost- and Dataset-free Stuck-at Fault Mitigation for ReRAM-based Deep Learning Accelerators.

[BibT_eX]

[DOI]

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

Automated Log-Scale Quantization for Low-Cost Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

IR-QNN Framework: An IR Drop-Aware Offline Training of Quantized Crossbar Arrays.

[BibT_eX]

[DOI]

IEEE Access, 2020

Architecture-Accuracy Co-optimization of ReRAM-based Low-cost Neural Network Processor.

[BibT_eX]

[DOI]

Proceedings of the GLSVLSI '20: Great Lakes Symposium on VLSI 2020, 2020

Learning to Predict IR Drop with Effective Training for ReRAM-based Neural Network Hardware.

[BibT_eX]

[DOI]

Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

2019

Double MAC on a DSP: Boosting the Performance of Convolutional Neural Networks on FPGAs.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2019

Successive Log Quantization for Cost-Efficient Neural Networks Using Stochastic Computing.

[BibT_eX]

[DOI]

Proceedings of the 56th Annual Design Automation Conference 2019, 2019

On-chip memory optimization for high-level synthesis of multi-dimensional data on FPGA.

[BibT_eX]

[DOI]

Daewoo Kim

Sugil Lee

Jongeun Lee

Proceedings of the 24th Asia and South Pacific Design Automation Conference, 2019

2018

Sign-magnitude SC: getting 10X accuracy for free in stochastic computing for deep neural networks.

[BibT_eX]

[DOI]

Proceedings of the 55th Annual Design Automation Conference, 2018

Sugil Lee

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