@inproceedings{5420204c342b422d9747562268b08102,
title = "POSTER: Accelerating High-Precision Integer Multiplication used in Cryptosystems with GPUs",
abstract = "High-precision integer multiplication is crucial in privacy-preserving computational techniques but poses acceleration challenges on GPUs due to its complexity and the diverse bit lengths in cryptosystems. This paper introduces GIM, an efficient high-precision integer multiplication algorithm accelerated with GPUs. It employs a novel segmented integer multiplication algorithm that separates implementation details from bit length, facilitating code optimizations. We also present a computation diagram to analyze parallelization strategies, leading to a series of enhancements. Experiments demonstrate that this approach achieves a 4.47× speedup over the commonly used baseline.",
keywords = "GPU computing, big integer multiplication",
author = "Zhaorui Zhang",
note = "Publisher Copyright: {\textcopyright} 2024 Copyright held by the owner/author(s).",
year = "2024",
month = mar,
day = "2",
doi = "10.1145/3627535.3638495",
language = "English",
series = "Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP",
pages = "445--447",
booktitle = "PPoPP 2024 - Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming",
}