基于空间的Java多核编程

S. Gudenkauf, W. Hasselbring
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引用次数: 5

摘要

多核处理器要求程序员尽可能地利用软件中的并发性。不幸的是,我们当前的并发抽象使得多核编程比必要时更加困难,因为我们必须在非常低的抽象级别上减少意外的非确定性,例如通过同步机制。在这篇经验论文中,我们分析了基于空间的系统是否可以减轻Java编程语言中的多核编程,并提出了协议编程模型,该模型引入了基于空间的活动组件编排,这些活动组件在内部编排细粒度的工作流活动。主要贡献有:(1)协议编程模型,(2)我们在不同的多核架构上评估的不同元组空间实现技术的可扩展性的基准测试结果,(3)两个等效的Mandelbrot应用程序的最佳情况测量的可扩展性的基准测试结果——一个用标准Java线程模型实现,一个用我们的协议编程模型实现。从这些实验中得出的结论是:(1)可以提供可合理扩展的元组空间数据结构;(2)至少对于所考虑的应用程序来说,协议带来的性能开销是为多核架构提供的编程便利性所做的合理权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Space-based multi-core programming in Java
Multi-core processors require programmers to exploit concurrency in software as far as possible. Unfortunately, our current concurrency abstractions make multi-core programming harder than necessary because we have to reduce unintended non-determinism on a very low level of abstraction, for instance via synchronisation mechanisms. In this experience paper we analyse if space-based systems can mitigate multi-core programming in the Java programming language and present the Procol programming model that introduces the space-based choreography of active components, which internally orchestrate fine-grained workflow activities. The main contributions are (1) the Procol programming model, (2) benchmark results of the scalability of different tuple space implementation techniques that we evaluated on different multi-core architectures, (3) benchmark results of the scalability of two equivalent Mandelbrot applications for best-case measurements -- one implemented with the standard Java thread model, one with our Procol programming model. The conclusions drawn from these experiments are (1) tuple space data structures that scale reasonably well can be provided, (2) the performance overhead that Procol imposes is at least for the considered application a reasonable trade-off for the ease of programming provided for multi-core architectures.
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