Implementation and Analysis of AES Encryption on GPU

High Performance Computing and Communication & 2012 IEEE 9th International Conference Embedded Software and Systems(2012)

引用 128|浏览6
暂无评分
摘要
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.
更多
查看译文
关键词
intel core,parellel computing,cipher feedback,advanced encryption standard,t-boxes,aes,ecb mode encoding process,electronic codebook,gpu,cryptography,parallel architectures,cuda implementation,graphics processing units,cbc mode decoding process,cuda,shared memory systems,aes encryption,on chip shared memory,aes algorithm,granularity,granular computing,nvidia tesla c2050 gpu,sequential implementation,cpu,gpu processing,gbps throughput,bytes aes block,throughput,encryption,kernel,instruction sets
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要