Implementation of bitsliced AES encryption on CUDA-Enabled GPU

Naoki Nishikawa, Hideharu Amano, Keisuke Iwai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)


Table-based implementations have been mainly reported in research related to high-performance AES on GPUs, in which tables are stored in the shared memory. On the other hand, this kind of implementations is subject to timing attacks, due to the latency required to access tables in the shared memory. Thanks to the increasing number of registers every year, GPU programming has enabled memory intensive applications such as bitsliced AES algorithm to be easily implemented. However, researches of implementation of bitsliced AES algorithm on GPU have not so far been conducted sufficiently in terms of several parameters. For this reason, in this paper, we present an implementation of bitsliced AES encryption on CUDA-enabled GPU with several parameters, especially focusing on three kinds of parallel processing granularities. According to the conducted experiments, the throughput of bitsliced AES-ECB encryption with Bs64 granularity achieves 605.9 Gbps on Nvidia Tesla P100-PCIe resulting in an enhancement of 8.0% when compared to the table-based implementation.

Original languageEnglish
Title of host publicationNetwork and System Security - 11th International Conference, NSS 2017, Proceedings
PublisherSpringer Verlag
Number of pages15
Volume10394 LNCS
ISBN (Print)9783319647005
Publication statusPublished - 2017
Event11th International Conference on Network and System Security, NSS 2017 - Helsinki, Finland
Duration: 2017 Aug 212017 Aug 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10394 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other11th International Conference on Network and System Security, NSS 2017


  • AES
  • Bitslice
  • Cryptography
  • CUDA
  • GPU

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Implementation of bitsliced AES encryption on CUDA-Enabled GPU'. Together they form a unique fingerprint.

Cite this