Department of Computer Science
Implementation and analysis of AES encryption on GPU
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. © 2012 IEEE.
AES, Cipher Feedback, CUDA, Electronic Codebook, GPU, Parellel computing
Source Publication Title
Proceedings of the The 14th IEEE International Conference on High Performance Computing and Communications/ The 9th IEEE International Conference on Embedded Software and Systems
Liverpool, United Kingdom
Link to Publisher's Edition
Li, Qinjian, Chengwen Zhong, Kaiyong Zhao, Xinxin Mei, and Xiaowen Chu. "Implementation and analysis of AES encryption on GPU." Proceedings of the The 14th IEEE International Conference on High Performance Computing and Communications/ The 9th IEEE International Conference on Embedded Software and Systems (2012): 843-848.