Parallel Algorithms for Sparse Matrix Multiplication and Join-Aggregate Queries

Xiao Hu, K. Yi
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引用次数: 2

Abstract

In this paper, we design massively parallel algorithms for sparse matrix multiplication, as well as more general join-aggregate queries, where the join hypergraph is a tree with arbitrary output attributes. For each case, we obtain asymptotic improvement over existing algorithms. In particular, our matrix multiplication algorithm is shown to be optimal in the semiring model.
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稀疏矩阵乘法和连接-聚合查询的并行算法
在本文中,我们设计了用于稀疏矩阵乘法的大规模并行算法,以及更一般的连接-聚合查询,其中连接超图是具有任意输出属性的树。对于每种情况,我们都得到了对现有算法的渐近改进。特别是,我们的矩阵乘法算法在半环模型中被证明是最优的。
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Probabilistic Databases for All Efficient Indexes for Diverse Top-k Range Queries Proceedings of the 39th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems Parallel Algorithms for Sparse Matrix Multiplication and Join-Aggregate Queries Deciding Robustness for Lower SQL Isolation Levels
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