Improving cryptanalytic applications with stochastic runtimes on GPUs and multicores

Abstract

We investigate cryptanalytic applications comprised of many independent tasks that exhibit a stochastic runtime distribution. We compare four algorithms for executing such applications on GPUs and on multicore CPUs with SIMD units. We demonstrate that for four different distributions, multiple problem sizes, and three platforms the best strategy varies. We support our analytic results by extensive experiments on an Intel Skylake-based multicore CPU and a high performance GPU (Nvidia Volta).