A Parallel Variant of LDSieve for the SVP on Lattices
A Parallel Variant of LDSieve for the SVP on Lattices
复制标题
格子上 SVP 的 LDSieve 并行变体
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
C. Bischof
中科院分区：
文献类型：
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作者：
Artur Mariano;Thijs Laarhoven;C. Bischof
在本文中，我们提出了Ldsieve的平行实现，Ldsieve是一种最近发布的Sieving算法，用于SVP，该算法达到了至今，直到今天，在并行共享内存系统上实现了最佳的理论复杂性。特别是，我们提出了一个可扩展的LDSieve的可扩展平行变体，该变体概率不受锁定，并放松算法的特性以偏爱并行性。我们使用LDSIVE的平行变体来回答与该算法有关的许多重要问题。特别是，我们表明，在共享内存系统上，LDSieve在相同甚至更少的执行时间内都比在随机晶格上使用的内存量相当好。
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.