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IMPROVING PERFORMANCE OF COLLECTIVE OPERATIONS: UPC CASE

机译:UPC案例,改善集体运营的绩效

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The collective operations of any parallel programming language involve more than one thread/process and act on multiple streams of data. The language's API provides both algorithmic and run-time system support to optimize the performance of these operations. Some developers, however, choose to play clever and start from the language's primitive operations and write their own versions of the collective operations. The question that always pops up: Are these developers wise? In this paper, we check the case of UPC (Universal Parallel C) and prove that in some circumstances, it is wiser for developers to optimize starting from UPC's primitive operations. In our testing we found out that optimization using primitive UPC operations by the developers can have better performance than readily available UPC's collective operations. In this paper, we pin point specific optimizations at both the algorithmic and the runtime support levels that developers could use to uncover missed optimization opportunities.
机译:任何并行编程语言的集体操作都涉及多个线程/进程,并作用于多个数据流。该语言的API提供了算法和运行时系统支持,以优化这些操作的性能。但是,某些开发人员选择发挥作用,从语言的原始操作开始,然后编写自己的集体操作版本。经常出现的问题:这些开发人员明智吗?在本文中,我们检查了UPC(通用并行C)的情况,并证明在某些情况下,开发人员从UPC的原始操作开始进行优化是更明智的选择。在我们的测试中,我们发现,开发人员使用原始的UPC操作进行的优化比可随时使用的UPC的集体操作具有更好的性能。在本文中,我们在开发人员可以用来发现错过的优化机会的算法和运行时支持级别上都指出了特定的优化。

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