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A basic-cycle calculation technique for efficient dynamic data redistribution

机译:高效动态数据重新分配的基本周期计算技术

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Array redistribution is usually required to enhance algorithm performance in many parallel programs on distributed memory multicomputers. Since it is performed at run-time, there is a performance trade-off between the efficiency of the new data decomposition for a subsequent phase of an algorithm and the cost of redistributing data among processors. In this paper, we present a basic-cycle calculation technique to efficiently perform BLOCK-CYCLIC(S) to BLOCK-CYCLIC(t) redistribution. The main idea of the basic-cycle calculation technique is, first, to develop closed forms for computing source/destination processors of some specific array elements in a basic-cycle, which is defined as icm(s,t)/gcd(s,t). These closed forms are then used to efficiently determine the communication sets of a basic-cycle. From the source/destination processor/data sets of a basic-cycle, we can efficiently perform a BLOCK-CYCLIC(s) to BLOCK-CYCLIC(t) redistribution. To evaluate the performance of the basic-cycle calculation technique, we have implemented this technique on an IBM SP2 parallel machine, along with the PITFALLS method and the multiphase method. The cost models for these three methods are also presented. The experimental results show that the basic-cycle calculation technique outperforms the PITFALLS method and the multiphase method for most test samples.
机译:通常需要使用数组重新分配来增强分布式内存多计算机上许多并行程序中的算法性能。由于它是在运行时执行的,因此在算法后续阶段的新数据分解效率与在处理器之间重新分配数据的成本之间存在性能折衷。在本文中,我们提出了一种基本周期计算技术,可以有效地执行从BLOCK-CYCLIC(S)到BLOCK-CYCLIC(t)的重新分配。基本周期计算技术的主要思想是,首先,为基本周期中的某些特定阵列元素的源/目标处理器的计算开发封闭形式,定义为icm(s,t)/ gcd(s, t)。这些封闭的形式然后被用来有效地确定基本周期的通信集合。从基本周期的源/目标处理器/数据集,我们可以有效地执行从BLOCK-CYCLIC到BLOCK-CYCLIC(t)的重新分配。为了评估基本周期计算技术的性能,我们已经在IBM SP2并行计算机上实现了该技术以及PITFALLS方法和多阶段方法。还介绍了这三种方法的成本模型。实验结果表明,对于大多数测试样品,基本周期计算技术的性能优于PITFALLS方法和多相方法。

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