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A fast, parallel spanning tree algorithm for symmetric multiprocessors (SMPS)

机译:用于对称多处理器(SMPS)的快速,并行生成树算法

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The ability to provide uniform shared-memory access to a significant number of processors in a single SMP node brings us much closer to the ideal PRAM parallel computer. Many PRAM algorithms can be adapted to SMPs with few modifications. Yet there are few studies that deal with the implementation and performance issues of running PRAM-style algorithms on SMPs. Our study in this paper focuses on implementing parallel spanning tree algorithms on SMPs. Spanning tree is an important problem in the sense that it is the building block for many other parallel graph algorithms and also because it is representative of a large class of irregular combinatorial problems that have simple and efficient sequential implementations and fast PRAM algorithms, but these irregular problems often have no known efficient parallel implementations. Experimental studies have been conducted on related problems (minimum spanning tree and connected components) using parallel computers, but only achieved reasonable speedup on regular graph topologies that can be implicitly partitioned with good locality features or on very dense graphs with limited numbers of vertices. In this paper we present a new randomized algorithm and implementation with superior performance that for the first time achieves parallel speedup on arbitrary graphs (both regular and irregular topologies) when compared with the best sequential implementation for finding a spanning tree. This new algorithm uses several techniques to give an expected running time that scales linearly with the number p of processors for suitably large inputs (n > p(2)). As the spanning tree problem is notoriously hard for any parallel implementation to achieve reasonable speedup, our study may shed new light on implementing PRAM algorithms for shared-memory parallel computers. The main results of this paper are1. A new and practical spanning tree algorithm for symmetric multiprocessors that exhibits parallel speedups on graphs with regular and irregular topologies; and2. an experimental study of parallel spanning tree algorithms that reveals the superior performance of our new approach compared with the previous algorithms.The source code for these algorithms is freely-available from our web site. (c) 2005 Elsevier Inc. All rights reserved.
机译:在单个SMP节点中提供对大量处理器的统一共享内存访问的能力使我们更加接近理想的PRAM并行计算机。许多PRAM算法几乎无需修改即可适用于SMP。但是,很少有研究涉及在SMP上运行PRAM风格算法的实现和性能问题。本文的研究重点是在SMP上实现并行生成树算法。从某种意义上讲,生成树是一个重要的问题,因为它是许多其他并行图算法的基础,并且因为它代表了一大类不规则组合问题,这些问题具有简单而有效的顺序实现和快速的PRAM算法,但是这些不规则问题问题通常没有已知的有效并行实现。已经使用并行计算机对相关问题(最小生成树和连接的组件)进行了实验研究,但仅在规则图拓扑上实现了合理的加速,规则图拓扑可以用良好的局部性特征进行隐式划分,或者在顶点数量有限的非常密集的图上。在本文中,我们提出了一种性能优越的新型随机算法和实现,与查找生成树的最佳顺序实现相比,该算法首次实现了任意图形(规则和不规则拓扑)上的并行加速。对于适当的大输入(n> p(2)),此新算法使用多种技术来给出预期的运行时间,该运行时间与处理器的数量p成线性比例。由于众所周知,对于任何并行实现而言,生成树问题都难以实现合理的加速,因此我们的研究可能为共享内存并行计算机实现PRAM算法提供新的思路。本文的主要结果是1。一种适用于对称多处理器的新颖实用的生成树算法,该算法在具有规则和不规则拓扑的图形上具有并行加速性能;和2。对并行生成树算法的实验研究表明,与以前的算法相比,我们的新方法具有更高的性能。这些算法的源代码可从我们的网站上免费获得。 (c)2005 Elsevier Inc.保留所有权利。

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