Run-time recognition of task parallelism within the P++ parallel array class library

R. Parsons, D. Quinlan
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引用次数: 32

Abstract

This paper explores the use of a run-time system to recognize task parallelism within a C++ array class library. Run-time systems currently support data parallelism in P++, FORTRAN 90 D, and High Performance FORTRAN. But data parallelism is insufficient for many applications, including adaptive mesh refinement. Without access to both data and task parallelism such applications exhibit several orders of magnitude more message passing and poor performance. In this paper, a C++ array class library is used to implement deferred evaluation and run-time dependence for task parallelism recognition, to obtain task parallelism through a data flow interpretation of data parallel array statements. Performance results show that the analysis and optimizations are both efficient and practical, allowing us to consider more substantial optimizations.<>
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p++并行数组类库中任务并行性的运行时识别
本文探讨了使用一个运行时系统来识别c++数组类库中的任务并行性。运行时系统目前在p++、FORTRAN 90d和高性能FORTRAN中支持数据并行。但是数据并行性对于许多应用来说是不够的,包括自适应网格细化。如果不能同时访问数据和任务并行性,这样的应用程序会表现出几个数量级的消息传递和较差的性能。本文利用c++数组类库实现任务并行性识别的延迟求值和运行时依赖,通过数据并行数组语句的数据流解释获得任务并行性。性能结果表明,分析和优化既有效又实用,使我们能够考虑更实质性的优化
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ScaLAPACK++: an object oriented linear algebra library for scalable systems The integrated library approach to parallel computing NHPDCC: The National High Performance Distributed Computing Consortium Parallel differential-algebraic equation solvers for power system transient stability analysis Scalable libraries for Fortran 90D/High Performance Fortran
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