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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：通用数组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：通用数组编程系统地从结构数组属性（例如形状和等级）中抽象出来。像往常一样，通用编程是以降低运行时性能为代价的。异步自适应专业化的思想是通过不断地将运行中的应用程序适应其数组的等级和形状，来利用并行计算工具来协调这些冲突的目标。我们的方法的有效性的一个关键参数是从请求某种专业化到其对正在运行的应用程序的可用性所花费的时间。我们描述了持久层的来龙去脉，该持久层将专用变体保留在存储库中以备将来使用，从而有效地将重新编译的平均等待时间减少到几乎为零。函数专业化和函数重载之间的相互影响等许多关键问题引起了我们的特别关注。我们通过一系列实验描述所采用的解决方案，并说明持久性异步自适应专业化的好处。

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