Lower bounds with smaller domain size on concurrent write parallel machines

J. Edmonds
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引用次数: 13

Abstract

The author proves an optimum lower bound, separating the PRIORITY and the COMMON PRAM models on a much more reasonably sized input domain than that shown by R.B. Boppana (1989). The proposed techniques provide a greater understanding of the partial information a processor learns about the input. For example, the author defines a new measure of the dependency that a function has on a variable and develops new set theoretic techniques to replace the use of Ramsey theory (which had forced the domain size to be large).<>
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并发写并行机上较小域大小的下界
作者证明了一个最优下界,在一个比R.B. Boppana(1989)所示的更合理的输入域上分离PRIORITY和COMMON PRAM模型。所提出的技术提供了对处理器学习的关于输入的部分信息的更好理解。例如,作者定义了函数对变量的依赖性的新度量,并开发了新的集合理论技术来取代Ramsey理论的使用(它迫使域的大小很大)。>
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