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首页> 外文期刊>International journal of parallel programming >Persistent Asynchronous Adaptive Specialization for Generic Array Programming
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Persistent Asynchronous Adaptive Specialization for Generic Array Programming

机译：通用阵列编程的持久异步自适应专业化

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摘要

Generic array programming systematically abstracts from structural array properties such as shape and rank. As usual, generic programming comes at the price of lower runtime performance. The idea of asynchronous adaptive specialization is to exploit parallel computing facilities to reconcile these conflicting objectives through the continuous adaptation of running applications to the ranks and shapes of their arrays. A key parameter for the effectiveness of our approach is the time it takes from requesting a certain specialization until its availability to the running application. We describe the ins and outs of a persistence layer that keeps specialized variants in a repository for future use and thus effectively reduces the average waiting time for re-compilation to nearly zero. A number of critical issues that, among others, stem from the interplay between function specialization and function overloading catch our special attention. We describe the solutions adopted and illustrate the benefits of persistent asynchronous adaptive specialization by a series of experiments.
机译：通用阵列编程系统地从结构阵列属性（如形状和等级）摘要。像往常一样，通用编程以较低的运行时性能的价格出现。异步自适应专业化的概念是利用并行计算设施来通过运行应用程序的持续调整来协调这些冲突的目标，以阵列的秩和形状。用于我们方法的有效性的关键参数是您需要在运行应用程序的可用性之前请求某种专业化所需的时间。我们描述了一个持久层的INS和OUT，它在存储库中保留专门的变体以供将来使用，从而有效地减少重新编译到接近零的平均等待时间。其中一些关键问题是，其中源于函数专业化和功能重载之间的相互作用，捕捉我们的特别关注。我们描述了通过一系列实验所采用和说明持续异步自适应专业化的优势。

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