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Synthesizing MPI Implementations from Functional Data-Parallel Programs

机译:从功能性数据并行程序综合MPI实现

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Distributed memory architectures such as Linux clusters have become increasingly common but remain difficult to program. We target this problem and present a novel technique to automatically generate data distribution plans, and subsequently MPI implementations in C++, from programs written in a functional core language. The main novelty of our approach is that we support distributed arrays, maps, and lists in the same framework, rather than just arrays. We formalize distributed data layouts as types, which are then used both to search (via type inference) for optimal data distribution plans and to generate the MPI implementations. We introduce the core language and explain our formalization of distributed data layouts. We describe how we search for data distribution plans using an adaptation of the Damas-Milner type inference algorithm, and how we generate MPI implementations in C++ from such plans.
机译:诸如Linux群集之类的分布式内存体系结构已变得越来越普遍,但仍然难以编程。我们针对此问题,并提出了一种新颖的技术,可以从以一种功能性核心语言编写的程序中自动生成数据分发计划,以及随后的C ++ MPI实现。我们方法的主要新颖之处在于,我们在同一框架中支持分布式数组,映射和列表,而不仅仅是数组。我们将分布式数据布局形式化为类型,然后将其用于搜索(通过类型推断)最佳数据分发计划并生成MPI实现。我们介绍了核心语言并解释了分布式数据布局的形式化。我们描述了如何使用Damas-Milner类型推断算法的改编来搜索数据分发计划,以及如何从此类计划中以C ++生成MPI实现。

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