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Extracting and implementing list homomorphisms in parallel program development

机译:在并行程序开发中提取和实现列表同构

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Homomorphisms are functions that match the divide-and-conquer pattem and are widely used in parallel programming. Two problems are studied for homomorphisms on lists: (l) parallelism extraction: finding a homomorphic representation of a given function; (2) parallelism implemen- tation deriving an efficient parallel program that computes the function. The proposed approach to parallelism extraction starts by whting tWo sequential programs for the function, on traditional cons lists and on dual snoc lists; the parallel program is obtained by generalizing sequential programs as terms. For almost-homomorphic functions, e.g., the maximum segment sum prob- lem, our method provides a systematic embedding into a homomorphism. The implementation problem is addressed by introducing the class of distributable homomorphisms and deriving for them a common parallel program schema. The derivation is based on equational reasoning in the Bird--Meertens formalism, which guarantees the correcturess of the parallel target program. The approach is illustrated with the function scan (parallel prefix), for which the combination of our two systematic methods yields the optimal hypercube algorithin, usually presented ad hoc in the literature.
机译:同态是匹配分治模式的函数,并广泛用于并行编程中。对于列表上的同态性,研究了两个问题:(l)并行性提取:找到给定函数的同态表示; (2)并行实现实现了一个可以计算功能的高效并行程序。提出的并行性提取方法首先在传统的缺点列表和双重snoc列表上花了两个顺序的函数程序;并行程序是通过将顺序程序概括为术语而获得的。对于几乎同胚的函数,例如最大片段和问题,我们的方法提供了系统嵌入同构的方法。通过引入可分配同态类并为其派生通用并行程序架构,可以解决实现问题。该推导基于Bird-Meertens形式主义中的方程式推理,可保证并行目标程序的正确性。通过功能扫描(并行前缀)说明了该方法,为此,我们两种系统方法的组合可产生最佳的超立方体算法,通常在文献中专门介绍。

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