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Parallel EARS edge addition rewrite systems

机译:并行EARS 边缘添加重写系统

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In this paper we show how edge addition rewrite systems (EARS) can be evaluated in parallel. EARS are a simple variant of graph rewrite systems, which only add edges to graphs. Because EARS are equivalent to a subset of Datalog, they provide a programming model for rule-based applications. EARS terminate and are strongly confluent, which makes them perfectly apt for parallel execution. In this paper we present two parallel evaluation methods, order-domain partitioning and evaluation on carrier-graphs. EARS provide scalable parallelism because efficient sequential evaluation techniques also exist.
机译:在本文中,我们展示了如何并行评估边缘加法重写系统(EARS)。 EARS是图形重写系统的简单变体,它仅向图形添加边。因为EARS等效于Datalog的子集,所以它们为基于规则的应用程序提供了编程模型。 EAR终止并且高度融合,这使它们非常适合并行执行。在本文中,我们提出了两种并行的评估方法:顺序域划分和对载波图的评估。 EARS还提供了可扩展的并行性,因为还存在有效的顺序评估技术。

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