The STAPL parallel container framework

Author:

Tanase Gabriel1,Buss Antal1,Fidel Adam1,Harshvardhan 1,Papadopoulos Ioannis1,Pearce Olga1,Smith Timmie1,Thomas Nathan1,Xu Xiabing1,Mourad Nedal2,Vu Jeremy1,Bianco Mauro1,Amato Nancy M.1,Rauchwerger Lawrence1

Affiliation:

1. Texas A&M University, College Station, TX, USA

2. KAUST, Thuwal, Saudi Arabia

Abstract

The Standard Template Adaptive Parallel Library (STAPL) is a parallel programming infrastructure that extends C++ with support for parallelism. It includes a collection of distributed data structures called pContainers that are thread-safe, concurrent objects, i.e., shared objects that provide parallel methods that can be invoked concurrently. In this work, we present the STAPL Parallel Container Framework (PCF), that is designed to facilitate the development of generic parallel containers. We introduce a set of concepts and a methodology for assembling a pContainer from existing sequential or parallel containers, without requiring the programmer to deal with concurrency or data distribution issues. The PCF provides a large number of basic parallel data structures (e.g., pArray, pList, pVector, pMatrix, pGraph, pMap, pSet). The PCF provides a class hierarchy and a composition mechanism that allows users to extend and customize the current container base for improved application expressivity and performance. We evaluate STAPL pContainer performance on a CRAY XT4 massively parallel system and show that pContainer methods, generic pAlgorithms, and different applications provide good scalability on more than 16,000 processors.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

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