A Parallel Variant of LDSieve for the SVP on Lattices

In this paper, we propose a parallel implementation of LDSieve, a recently published sieving algorithm for the SVP, which achieves the best theoretical complexity to this day, on parallel shared-memory systems. In particular, we propose a scalable parallel variant of LDSieve that is probabilistically lock-free and relaxes the properties of the algorithm to favour parallelism. We use our parallel variant of LDSieve to answer a number of important questions pertaining to the algorithm. In particular, we show that LDSieve scales fairly well on shared-memory systems and uses much less memory than HashSieve on random lattices, for the same or even less execution time.