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 sharedmemory systems and uses much less memory than HashSieve on random lattices, for the same or even less execution time.