论文标题
最大原子不繁殖集：基于用法的数据流分区算法
Maximal Atomic irRedundant Sets: a Usage-based Dataflow Partitioning Algorithm
论文作者
论文摘要
承认多面体表示的程序可以通过多种方式转化为地方性和并行性，尤其是循环瓷砖。然后，数据流分析可以计算迭代之间和图块之间的依赖关系。应用平铺时，在某些迭代方面依赖性跨瓷砖边界，创造了瓷砖间数据通信的需求。以前的工作将其计算为迭代图块的流入和流出集合。 在本文中，我们提出了将瓷砖流出到最大迭代集中的划分，这些迭代完全被消耗掉，并且没有产生冗余的存储或转移。该计算被描述为算法，并在选择多面体程序上进行。然后，我们建议该分解在压缩和内存分配中的可能应用。
Programs admitting a polyhedral representation can be transformed in many ways for locality and parallelism, notably loop tiling. Data flow analysis can then compute dependence relations between iterations and between tiles. When tiling is applied, certain iteration-wise dependences cross tile boundaries, creating the need for inter-tile data communication. Previous work computes it as the flow-in and flow-out sets of iteration tiles. In this paper, we propose a partitioning of the flow-out of a tile into the maximal sets of iterations that are entirely consumed and incur no redundant storage or transfer. The computation is described as an algorithm and performed on a selection of polyhedral programs. We then suggest possible applications of this decomposition in compression and memory allocation.
