Accelerating Finite Field Arithmetic for Homomorphic Encryption on GPUs-Reference-Cited by-同舟云学术

Accelerating Finite Field Arithmetic for Homomorphic Encryption on GPUs

Published:2023-09 Issue:5 Volume:43 Page:55-63
ISSN:0272-1732
Container-title:IEEE Micro
language:
Short-container-title:IEEE Micro

Author:

Livesay Neal¹^ORCID,Jonatan Gilbert²^ORCID,Mora Evelio³^ORCID,Shivdikar Kaustubh¹^ORCID,Agrawal Rashmi⁴^ORCID,Joshi Ajay⁴^ORCID,Abellán José L.⁵^ORCID,Kim John²^ORCID,Kaeli David¹^ORCID

Affiliation:

1. Northeastern University, Boston, MA, USA

2. Korea Advanced Institute of Science and Technology University, Daejeon, South Korea

3. Universidad Católica de Murcia, Guadalupe, Murcia, Spain

4. Boston University, Boston, MA, USA

5. Universidad de Murcia, Murcia, Spain

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

Link

https://ieeexplore.ieee.org/ielam/40/10248411/10068510-aam.pdf

Reference12 articles.

1. High-Performance Ideal Lattice-Based Cryptography on 8-Bit ATxmega Microcontrollers

2. OpenFHE

3. Accelerating Number Theoretic Transformations for Bootstrappable Homomorphic Encryption on GPUs

4. Faster arithmetic for number-theoretic transforms

5. Implementing the Rivest Shamir and Adleman Public Key Encryption Algorithm on a Standard Digital Signal Processor

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2. GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption;56th Annual IEEE/ACM International Symposium on Microarchitecture;2023-10-28

3. A Survey of Software Implementations for the Number Theoretic Transform;Lecture Notes in Computer Science;2023