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IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum : [proceedings]. IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum最新文献

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Last alternative optimization 最后备选优化
G. Gupta, Enrico Pontelli
The authors present a new optimization for or-parallel logic programming (Prolog) systems, called last alternative optimization (LAO). The LAO follows from the flattening principle and the principle of duality of or-parallelism and and-parallelism. Originally LAO was conceived as the dual of last parallel call optimization, an optimization developed for and-parallel systems. LAO enables Prolog programs that have data-or parallelism to execute more efficiently. It also enables more efficient (parallel) execution of constraint logic programs over finite domains. LAO is a fairly general optimization and can be readily applied to virtually any parallel system that exploits nondeterminism (e.g., parallel search based artificial intelligence systems). Last alternative optimization has been implemented in the ACE parallel Prolog system. The performance results indeed prove the effectiveness of LAO. They present a second optimization based on the flattening principle, called balanced nesting optimization (BNO), that is related to LAO, and that also leads to reduction of parallel overhead.
作者提出了一种新的或并行逻辑编程(Prolog)系统优化方法,称为最后可选优化(LAO)。LAO遵循平坦原则和或平行、并平行的对偶原则。最初,LAO被认为是最后一个并行调用优化的对偶,这是为并行系统开发的一种优化。LAO使具有数据或并行性的Prolog程序能够更有效地执行。它还支持在有限域内更有效地(并行)执行约束逻辑程序。LAO是一种相当通用的优化,可以很容易地应用于几乎任何利用不确定性的并行系统(例如,基于人工智能系统的并行搜索)。最后在ACE并行Prolog系统中实现了备选优化。性能结果确实证明了LAO的有效性。他们提出了基于扁平化原则的第二种优化,称为平衡嵌套优化(BNO),它与LAO相关,也可以减少并行开销。
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引用次数: 6
Data parallel logic programming in &ACE 数据并行逻辑编程&ACE
Enrico Pontelli, G. Gupta
&ACE is a high performance parallel Prolog system developed at the Laboratory for Logic, Databases, and Advanced Programming that exploits and-parallelism from Prolog programs. &ACE was developed to exploit MIMD parallelism. However, SPMD parallelism also arises naturally in many Prolog programs. In this paper we develop runtime techniques that allow systems that have primarily been designed to exploit MIMD parallelism (such as &ACE) to also efficiently exploit SPMD parallelism. These runtime techniques have been incorporated in the &ACE system. Performance of &ACE augmented with these techniques on programs containing SPMD parallelism is presented.
&ACE是由逻辑、数据库和高级编程实验室开发的高性能并行Prolog系统,它利用了Prolog程序的并行性。开发&ACE是为了利用MIMD并行性。然而,SPMD并行性在许多Prolog程序中也会自然出现。在本文中,我们开发了运行时技术,允许主要设计用于利用MIMD并行性的系统(如&ACE)也有效地利用SPMD并行性。这些运行时技术已经被整合到&ACE系统中。给出了这些技术增强的&ACE在包含SPMD并行性的程序上的性能。
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引用次数: 7
Asynchronous parallel search by the parallel genetic algorithm 采用并行遗传算法进行异步并行搜索
H. Mühlenbein
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引用次数: 1
期刊
IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum : [proceedings]. IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum
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