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Interprocedural Transformations for Extracting Maximum Parallelism

机译:提取最大并行度的过程间转换

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Since most program execution time is consumed in loop structure, we propose a data dependency elimination method which extracts maximum parallelism from the sequential loop. This procedure automatically transforms nested loops to nested DOALL loops, thereby reduces data dependency effectively. Conventional studies for extracting the parallelism are focused mostly on a single procedure transition. But almost all programs have potential parallelisms among multiple procedures. Procedure call parallelisms, with only a single loop structure or procedure call, almost all are concerned with the uniform code within the uniform data dependency distance. In this study, we propose an algorithm which can be applied to uniform, nonuniform, and complex data dependency distance among multiple procedures. For the performance evaluation, we compare loop extraction, loop embedding, and procedure cloning using CRAY-T3E. The results show that the proposed algorithm is effective.
机译:由于大多数程序执行时间都消耗在循环结构中,因此我们提出了一种数据依赖消除方法,该方法从顺序循环中提取最大并行度。此过程将嵌套循环自动转换为嵌套DOALL循环,从而有效降低了数据依赖性。提取并行性的常规研究主要集中在单个过程转换上。但是几乎所有程序在多个过程之间都有潜在的并行性。仅具有单个循环结构或过程调用的过程调用并行性,几乎所有都与统一数据相关性范围内的统一代码有关。在这项研究中,我们提出了一种算法,该算法可以应用于多个过程之间的均匀,不均匀和复杂的数据依赖距离。为了进行性能评估,我们比较了使用CRAY-T3E进行的循环提取,循环嵌入和过程克隆。结果表明,该算法是有效的。

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