Paper 2016/471

NTRU Modular Lattice Signature Scheme on CUDA GPUs

Wei Dai and John Schanck and Berk Sunar and William Whyte and Zhenfei Zhang

Abstract

In this work we show how to use Graphics Processing Units (GPUs) with Compute Unified Device Architecture (CUDA) to accelerate a lattice based signature scheme, namely, the NTRU modular lattice signature (NTRU-MLS) scheme. Lattice based schemes require operations on large vectors that are perfect candidates for GPU implementations. In addition, similar to most lattice based signature schemes, NTRU-MLS provides transcript security with a rejection sampling technique. With a GPU implementation, we are able to generate many candidates simultaneously, and hence mitigate the performance slowdown from rejection sampling. Our implementation results show that for the original NTRU-MLS parameter sets, we obtain a 2x improvement in the signing speed; for the revised parameter sets, where acceptance rate of rejection sampling is down to around 1%, our implementation can be as much as 47x faster than a CPU implementation.