Implementation and Analysis of AES Encryption on GPU

Qinjian Li, Chengwen Zhong, Kaiyong Zhao, Xinxin Mei, Xiaowen Chu
Center for High Performance Computing, Northwestern Polytechnical University, Xi’an, CHINA
The third International Workshop on Frontier of GPU Computing, 2012


   title={Implementation and Analysis of AES Encryption on GPU},

   author={Li, Q. and Zhong, C. and Zhao, K. and Mei, X. and Chu, X.},



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GPU is continuing its trend of vastly outperforming CPU while becoming more general purpose. In order to improve the efficiency of AES algorithm, this paper proposed a CUDA implementation of Electronic Codebook (ECB) mode encoding process and Cipher Feedback (CBC) mode decoding process on GPU. In our implementation, the frequently accessed T-boxes were allocated on on-chip shared memory and the granularity that one thread handles a 16 Bytes AES block was adopted. Finally, we achieved the highest performance of around 60 Gbps throughput on NVIDIA Tesla C2050 GPU, which runs up to 50 times faster than a sequential implementation based on Intel Core i7-920 2.66GHz CPU. In addition, we discussed the optimization under some practical application scenarios such as overlapping GPU processing and data transfer.
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