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Automatically Generating Instruction Selectors Using Declarative Machine Descriptions

机译:使用声明性机器描述自动生成指令选择器

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摘要

Despite years of work on retargetable compilers, creating a good, reliable back end for an optimizing compiler still entails a lot of hard work. Moreover, a critical component of the back end-the instruction selector-must be written by a person who is expert in both the compiler's intermediate code and the target machine's instruction set. By generating the instruction selector from declarative machine descriptions we have (a) made it unnecessary for one person to be both a compiler expert and a machine expert, and (b) made creating an optimizing back end easier than ever before. Our achievement rests on two new results. First, finding a mapping from intermediate code to machine code is an undecidable problem. Second, using heuristic search, we can find mappings for machines of practical interest in at most a few minutes of CPU time. Our most significant new idea is that heuristic search should be controlled by algebraic laws. Laws are used not only to show when a sequence of instructions implements part of an intermediate code, but also to limit the search: we drop a sequence of instructions not when it gets too long or when it computes too complicated a result, but when too much reasoning will be required to show that the result computed might be useful.
机译:尽管有多年的重新谋取编译器,但为优化编译器创建了一个好的,可靠的后端,仍然需要很多努力工作。此外,后端 - 指令选择器的关键组件 - 必须由编译器中间代码和目标机器指令集的专家编写。通过从声明性机器描述中生成指令选择器,我们(a)使一个人成为编译器专家和机器专家,并且(b)使得比以往任何时候都更容易创建优化。我们的成就依赖于两个新结果。首先,从中间代码找到到机器代码的映射是一个未定定的问题。其次,使用启发式搜索,我们可以在最多几分钟的CPU时间找到实际兴趣的机器映射。我们最重要的新想法是启发式搜索应该由代数法控制。不仅使用了一系列指令何时实现中间代码的一部分的法律,还可以限制搜索:我们删除了一系列指令,而不是太长或计算它的结果太复杂,但何时也是如此将需要许多推理来表明计算的结果可能是有用的。

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