High-speed GPU implementation of a secret sharing scheme based on cellular automata

Parallel implementation provides a solution for the problem of accelerating cellular automata (CA)-based secret sharing schemes and make them appropriate for bulk data sharing and real-time applications. By presenting new platforms, we need new implementation techniques to run algorithms as fast as possible on the platform. In this paper, we present a new implementation of a CA-based secret sharing scheme using the Graphic Processing Unit (GPU). We propose a new data arrangement that reduces the total number of accesses to the memories in GPU. Our algorithm further reduces the amount of data required by each thread and at the same time achieves a high cache hit rate. Also, it can achieve coalesced memory accesses to optimal use of the global memory bandwidth. The proposed method obtains speedup up to four times faster than the best previous GPU implemented CA-based multi-secret sharing schemes.