Sangpyo Kim

Orcid: 0000-0001-9477-6683

According to our database1, Sangpyo Kim authored at least 12 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
HyPHEN: A Hybrid Packing Method and Its Optimizations for Homomorphic Encryption-Based Neural Networks.
IEEE Access, 2024

2023
Toward Practical Privacy-Preserving Convolutional Neural Networks Exploiting Fully Homomorphic Encryption.
CoRR, 2023

CiFHER: A Chiplet-Based FHE Accelerator with a Resizable Structure.
CoRR, 2023

HyPHEN: A Hybrid Packing Method and Optimizations for Homomorphic Encryption-Based Neural Networks.
CoRR, 2023

SHARP: A Short-Word Hierarchical Accelerator for Robust and Practical Fully Homomorphic Encryption.
Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023

2022
ARK: Fully Homomorphic Encryption Accelerator with Runtime Data Generation and Inter-Operation Key Reuse.
Proceedings of the 55th IEEE/ACM International Symposium on Microarchitecture, 2022

BTS: an accelerator for bootstrappable fully homomorphic encryption.
Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022

2021
Over 100x Faster Bootstrapping in Fully Homomorphic Encryption through Memory-centric Optimization with GPUs.
IACR Trans. Cryptogr. Hardw. Embed. Syst., 2021

Accelerating Fully Homomorphic Encryption Through Architecture-Centric Analysis and Optimization.
IEEE Access, 2021

Accelerating Fully Homomorphic Encryption Through Microarchitecture-Aware Analysis and Optimization.
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2021

2020
HEAAN Demystified: Accelerating Fully Homomorphic Encryption Through Architecture-centric Analysis and Optimization.
CoRR, 2020

Accelerating Number Theoretic Transformations for Bootstrappable Homomorphic Encryption on GPUs.
Proceedings of the IEEE International Symposium on Workload Characterization, 2020


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