Associative Parallel Containers in STAPL
Associative Parallel Containers in STAPL
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STAPL 中的关联并行容器
DOI：
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发表时间：
2007
期刊：
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通讯作者：
Lawrence Rauchwerger
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作者：
Ilie Gabriel Tanase;C. Raman;Mauro Bianco;N. Amato;Lawrence Rauchwerger
标准模板自适应并行库（Stapl）是一个并行编程框架，可扩展C ++和STL并支持并行性。 Stapl提供了并行数据结构（PCONTAINERS）和算法（Palgorithms）的集合，以及用于扩展它们以提供自定义功能的通用方法。 stapl pcontainers是线程安全，并发对象，即提供可以同时调用的并行方法的共享对象。他们还提供了适当的接口，可以通过通用的载体使用。在这项工作中，我们介绍了Stapl关联PContainers的设计和实现：PMAP，PSET，PMULTIMAP，PMULTIMAP，PMULTISET，PHASHMAP和PHASHSET。这些容器为基于密钥的分布式元素集合提供了最佳插入，搜索和删除操作。他们的方法包括STL关联容器提供的方法的对应物，以及一些异步（非阻滞）变体，这些变体可以并行提供改进的性能。我们在IBM Power5群集，IBM Power3群集和基于Linux的Opteron群集上评估Stapl关联PContainers的性能，并显示新的PContainer asynchronous方法，通用的Palgorithms（例如，基于基于排序的应用程序）和基于排序应用程序在关联PContainers上，所有这些都可以为超过103个过程提供良好的可扩展性。
The Standard Template Adaptive Parallel Library ( stapl ) is a parallel programming framework that extends C++ and stl with support for parallelism. stapl provides a collection of parallel data structures ( pContainers ) and algorithms ( pAlgorithms ) and a generic methodology for extending them to provide customized functionality. stapl pContainers are thread-safe, concurrent objects, i.e., shared objects that provide parallel methods that can be invoked concurrently. They also provide appropriate interfaces that can be used by generic pAlgorithms . In this work, we present the design and implementation of the stapl associative pContainers : pMap , pSet , pMultiMap , pMultiSet , pHashMap , and pHashSet . These containers provide optimal insert, search, and delete operations for a distributed collection of elements based on keys. Their methods include counterparts of the methods provided by the stl associative containers, and also some asynchronous (non-blocking) variants that can provide improved performance in parallel. We evaluate the performance of the stapl associative pContainers on an IBM Power5 cluster, an IBM Power3 cluster, and on a linux-based Opteron cluster, and show that the new pContainer asynchronous methods, generic pAlgorithms (e.g., pfind ) and a sort application based on associative pContainers , all provide good scalability on more than 103processors.