An efficient and scalable postcomputation-based generic-point parallel scalar multiplication method

An efficient generic-point parallel scalar multiplication method is presented here where a new mapping technique is used with a modified version of the postcomputation-based method [6]. The results show that the proposed method outperforms that of the work in [6] when the number of consecutive requests is two or more. Furthermore, the results show that the proposed method is scalable for any number of parallel processors and performs better as the number of consecutive requests increases. This method consequently is very attractive for use in high-performance end servers that employ parallel elliptic curve processors.