Associative Parallel Containers in STAPL

  • Authors:

  • Gabriel Tanase;Chidambareswaran Raman;Mauro Bianco;Nancy M. Amato;Lawrence Rauchwerger

  • Affiliations:

  • Parasol Lab, Dept. of Computer Science, Texas A&M University,;Parasol Lab, Dept. of Computer Science, Texas A&M University,;Parasol Lab, Dept. of Computer Science, Texas A&M University,;Parasol Lab, Dept. of Computer Science, Texas A&M University,;Parasol Lab, Dept. of Computer Science, Texas A&M University,

  • Venue:
  • Languages and Compilers for Parallel Computing
  • Year:
  • 2007

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Abstract

The Standard Template Adaptive Parallel Library (stapl) is a parallel programming framework that extends C++ and stlwith support for parallelism. staplprovides a collection of parallel data structures (pContainers) and algorithms (pAlgorithms) and a generic methodology for extending them to provide customized functionality. staplpContainersare 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 staplassociative 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 stlassociative containers, and also some asynchronous (non-blocking) variants that can provide improved performance in parallel. We evaluate the performance of the staplassociative pContainerson an IBM Power5 cluster, an IBM Power3 cluster, and on a linux-based Opteron cluster, and show that the new pContainerasynchronous methods, generic pAlgorithms(e.g., pfind) and a sort application based on associative pContainers, all provide good scalability on more than 103processors.