数组语言中融合与收缩的实现与计算

Christopher M. Lewis, C. Liny, L. Snyder
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引用次数: 65

摘要

数组语言如Fortran 90、HPF和ZPL在简化基于数组的计算和表达数据并行性方面有很多好处。然而,它们可能会遭受很大的性能损失,因为它们引入了中间数组——无论是在源代码级别还是在编译过程中——这会增加内存使用并污染缓存。大多数编译器通过简单地缩放数组语言并依赖标量语言编译器来执行循环融合和数组收缩来解决这个问题。相反,我们展示了在数组级别执行循环融合和数组收缩形式的优点。本文介绍了这种方法,并说明了它的优点。实验结果表明,我们的方案通常可以使运行时间提高20%以上,有时甚至高达400%。此外,与商业编译器相比,它产生了更好的内存使用,与标量语言相比,它显示了相当的内存使用。我们还探讨了这些转换和通信优化之间的交互。
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The implementation and evaluation of fusion and contraction in array languages
Array languages such as Fortran 90, HPF and ZPL have many benefits in simplifying array-based computations and expressing data parallelism. However, they can suffer large performance penalties because they introduce intermediate arrays---both at the source level and during the compilation process---which increase memory usage and pollute the cache. Most compilers address this problem by simply scalarizing the array language and relying on a scalar language compiler to perform loop fusion and array contraction. We instead show that there are advantages to performing a form of loop fusion and array contraction at the array level. This paper describes this approach and explains its advantages. Experimental results show that our scheme typically yields runtime improvements of greater than 20% and sometimes up to 400%. In addition, it yields superior memory use when compared against commercial compilers and exhibits comparable memory use when compared with scalar languages. We also explore the interaction between these transformations and communication optimizations.
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