About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
PDP 2017
Conference paper
A Parallel Variant of LDSieve for the SVP on Lattices
Abstract
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.