Terabit encryption in a second: Performance evaluation of block ciphers in GPU with Kepler, Maxwell, and Pascal architectures

With the emergence of IoT and cloud computing technologies, massive data are generated from various applications everyday and communicated through the Internet. Secure communication is essential to protect these data from malicious attacks. Block ciphers are one mechanism to offer such protection but unfortunately involve intensive computations that can be performance bottlenecks to the servers, especially when the data center needs to handle thousands of concurrent transactions. In this paper, we investigate the feasibility of the GPU as an accelerator to perform high-speed encryption in server environments. We present optimized implementations of a conventional block cipher (AES) and new lightweight block ciphers (LEA, Chaskey, SIMON, SPECK, and SIMECK) across three new GPU architectures (Kepler, Maxwell, and Pascal). For AES, we improve the fine-grain implementation by utilizing the warp shuffle instruction available in these three new GPU architectures, which yield a 6%-16% improvement over the previous implementations. For LEA, Chaskey, SIMON, SPECK, and SIMECK, we first analyze why they cannot have efficient fine-grain implementations in the GPU and then present our optimization techniques, which are able to achieve impressive encryption speeds of 1.912, 637, 1.485, 2.291, and 1.478 Tb/s, respectively, in GTX1080.