Olivia Chen
Orcid: 0000-0002-2208-0262
According to our database1,
Olivia Chen
authored at least 23 papers
between 2019 and 2024.
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Bibliography
2024
Extremely Energy-Efficient Non-Linear Function Approximation Framework Using Stochastic Superconductor Devices.
IEEE Trans. Emerg. Top. Comput., 2024
SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024
2023
A Life-Cycle Energy and Inventory Analysis of Adiabatic Quantum-Flux-Parametron Circuits.
CoRR, 2023
Design and Implementation of an FFT-Based Neural Network Accelerator Using Rapid Single-Flux-Quantum Technology.
Proceedings of the 21st IEEE Interregional NEWCAS Conference, 2023
SupeRBNN: Randomized Binary Neural Network Using Adiabatic Superconductor Josephson Devices.
Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, 2023
Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023
Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023
A Global Optimization Algorithm for Buffer and Splitter Insertion in Adiabatic Quantum-Flux-Parametron Circuits.
Proceedings of the 28th Asia and South Pacific Design Automation Conference, 2023
Performance Assessment of an Extremely Energy-Efficient Binary Neural Network Using Adiabatic Superconductor Devices.
Proceedings of the 5th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2023
2022
Design and Implementation of Stochastic Neural Networks Using Superconductor Quantum-Flux-Parametron Devices.
Proceedings of the 35th IEEE International System-on-Chip Conference, 2022
A Study on the Efficient Design of Adders Using Adiabatic Quantum-Flux-Parametron Circuits.
Proceedings of the 11th IEEE Global Conference on Consumer Electronics, 2022
A Neural Network Processing Unit Using Adiabatic Quantum-Flux-Parametron Superconducting Technology.
Proceedings of the 11th IEEE Global Conference on Consumer Electronics, 2022
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022
2021
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021
2020
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020
2019
A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology.
CoRR, 2019
IDE Development, Logic Synthesis and Buffer/Splitter Insertion Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.
Proceedings of the 2019 IEEE Computer Society Annual Symposium on VLSI, 2019
A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology.
Proceedings of the 46th International Symposium on Computer Architecture, 2019
A Buffer and Splitter Insertion Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.
Proceedings of the 37th IEEE International Conference on Computer Design, 2019
A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.
Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019