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Loop Parallelization in Multi-dimensional Cartesian Space

机译:多维笛卡尔空间中的循环并行化

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摘要

Loop parallelization is of great importance to automatic translation of sequential into parallel code. We have applied Diophantine equations to compute the basic dependency vector sets covering all possible non-uniform dependencies between loop iterations. To partition the resultant dependencies space into multi-dimensional tiles of suitable shape and size, a new genetic algorithm is proposed in this article. Also, a new scheme based on multidimensional wave-fronts is developed to convert the multi-dimensional parallelepiped tiles into parallel loops. The problem of determining optimal tiles is NP-hard. Presenting a new constraint genetic algorithm in this paper the tiling problem is for the first time solved, in Cartesian spaces of any dimensionality.
机译:循环并行化对于将顺序自动转换为并行代码非常重要。我们已经应用了Diophantine方程来计算基本的依赖关系向量集,该向量集涵盖了循环迭代之间所有可能的非均匀依赖关系。为了将得到的依存空间划分为适当形状和大小的多维图块,本文提出了一种新的遗传算法。另外,开发了一种基于多维波前的新方案,将多维平行六面体瓦片转换成并行回路。确定最优图块的问题是NP难的。本文提出了一种新的约束遗传算法,首次解决了在任意维度的笛卡尔空间中的平铺问题。

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