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A Hyperplane Based Approach for Optimizing Spatial Locality in Loop Nests

机译:基于超平面的环巢空间局部性优化方法

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This paper presents a data layout optimization technique based on the theory of hyperplanes from linear algebra. Given a program, our framework automatically determines the optimal layouts that can be expressed by hyperplanes for each array that is referenced. We discuss the cases where data transformations are preferable to loop transformations and show that under specific conditions a loop nest can be optimized for perfect spatial locality by using data transformations. We divide the problem of optimizing data layout into two independent subproblems: (1) determining optimal layouts, and (2) determining data transformation matrices to implement optimal layouts. By postponing the determination of the transformation matrix to the last stage, our method can be adapted to compilers with different default layouts. Our results on eight programs on SGI Origin 2000 distributed-shared-memory multiprocessor show that the layout optimizations are effective in optimizing spatial locality.
机译:本文提出了一种基于线性代数超平面理论的数据布局优化技术。给定一个程序,我们的框架会自动为每个被引用的阵列确定可以由超平面表示的最佳布局。我们讨论了数据转换比循环转换更可取的情况,并显示了在特定条件下,可以通过使用数据转换来优化循环嵌套以实现完美的空间局部性。我们将优化数据布局的问题分为两个独立的子问题:(1)确定最佳布局,以及(2)确定数据转换矩阵以实现最佳布局。通过将转换矩阵的确定推迟到最后阶段,我们的方法可以适用于具有不同默认布局的编译器。我们在SGI Origin 2000分布式共享内存多处理器上的八个程序上的结果表明,布局优化可以有效地优化空间局部性。

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