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Efficient Code Generation for Automatic Parallelization and Optimization

机译:有效的代码生成自动并行化和优化

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Supercompilers look for the best execution order of the statement instances in the most compute intensive kernels. It has been extensively shown that the polyhedral model provides convenient abstractions to find and perform the useful program transformations. Nevertheless, the current polyhedral code generation algorithms lack for flexibility by adressing mainly unimodular or at least invertible transformation functions. Moreover, their complexity is challenging for large problems (with many statements). In this paper, we discuss a general transformation framework able to deal with non-unimodular, non-invertible functions. A completed and improved version of one of the best algorithms known so far is presented to actually perform the code generation. Experimental evidence proves the ability of our framework to handle real-life problems.
机译:SuperCompilers在最粗细计算的密集内核中查找语句实例的最佳执行顺序。它已被广泛表明多面体模型提供方便的抽象来查找和执行有用的程序转换。尽管如此,目前的多面体代码生成算法通过主要是单模或至少可逆的转换功能来利用缺乏灵活性。此外,他们的复杂性对大问题(许多陈述)有挑战性。在本文中,我们讨论了一种能够处理非单模不可逆功能的一般转型框架。到目前为止已知的最佳算法之一的完整和改进版本以实际执行代码生成。实验证据证明了我们框架处理现实生活问题的能力。

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