A Parallel GPU Implementation of SWIFFTX

Date

2020-01-01

Author

Ulu, Metin Evrim
Cenk, Murat

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The SWIFFTX algorithm is one of the candidates of SHA-3 Hash Competition that uses the number theoretic transform (NTT). It has 256-byte input blocks and 65-byte output blocks. In this paper, a parallel implementation of the algorithm and particular techniques to make it faster on GPU are proposed. We target version 6.1 of NVIDIA®CUDA™compute architecture that employs an ISA (Instruction Set Architecture) called Parallel Thread Execution (PTX) which possesses special instrinsics, hence we modify the reference implementation for better results. Experimental results indicate almost 10x improvement in speed and 5 W decrease in power consumption per 216 hashes.

Subject Keywords

Hash function, SWIFFTX, SHA-3, NTT, GPU, CUDA

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85083701099&origin=inward
https://hdl.handle.net/11511/90402

DOI

https://doi.org/10.1007/978-3-030-43120-4_16

Conference Name

8th International Conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2019

Collections

Graduate School of Applied Mathematics, Conference / Seminar

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Citation Formats

M. E. Ulu and M. Cenk, “A Parallel GPU Implementation of SWIFFTX,” presented at the 8th International Conference on Mathematical Aspects of Computer and Information Sciences, MACIS 2019, Gebze, Türkiye, 2020, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85083701099&origin=inward.