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Dealing with data dependent conditions to enable general global source code transformations

机译:处理数据相关的条件以实现常规的全局源代码转换

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摘要

Global source code transformations, such as Global Loop Transformations (GLT), are usually performed on a Geometrical Model (GM) which is very effective in dealing with complex transformations. However, this model imposes strict limitations on the input code, and it is not capable to deal with data dependent conditions. The technique presented in this paper can deal with data dependent conditions at any loop level. At the outermost loop level hot code paths are grouped together into limited number of clusters called scenarios to maximise the GLT benefit for a given code size growth. On the middle and innermost loop level we manipulate the abstract syntax tree to move the data dependent conditions out of the GLT optimisation scope. Results show up to 45.8% improvement compared to state-of-the-art.
机译:全局源代码转换(例如全局循环转换(GLT))通常在几何模型(GM)上执行,这在处理复杂转换方面非常有效。但是,此模型对输入代码施加了严格的限制,并且无法处理依赖数据的条件。本文介绍的技术可以处理任何循环级别的数据相关条件。在最外层的循环级别,热代码路径被组合到称为场景的有限数量的群集中,以在给定代码大小增长的情况下最大程度地提高GLT收益。在最中间和最内部的循环级别,我们操纵抽象语法树将依赖数据的条件移出GLT优化范围。结果显示,与最新技术相比,性能提高了45.8%。

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