Global schedulers are components in parallel runtime libraries that distribute the application's workload across physical resources. More often than not, applications showcase dynamic load imbalance and require customized scheduling solutions to avoid wasting resources. Some libraries lack support for user-defined schedulers and developers resort to unofficial extensions that are harder to reuse and maintain. We propose a global scheduler software design, entitled ARTful model, to create user-defined solutions with minimal alterations in the runtime library. Our model uses a component-based design to separate components from the runtime library and the scheduling policy implementation. The ARTful modeldescribes the interface of a portable scheduler library, allowing policies to operate on different runtime libraries. We study the overhead induced by our design through our ARTful library implementation metaprogramming-oriented global scheduling library using workload-aware scheduling policies. We experiment with two different policies from OpenMP and Charm++ runtime systems, also presenting evaluations of the policies outside of their original library context. We observe that our portable schedulers can sometimes perform decisions faster than their native counterparts with negligible overhead in the execution times of synthetic applications and molecular dynamics kernels.

中文翻译：

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ARTful：针对多个高性能计算运行时系统的用户定义调度器模型

全局调度程序是并行运行时库中的组件，用于跨物理资源分配应用程序的工作负载。通常情况下，应用程序会表现出动态负载不平衡，并需要定制的调度解决方案以避免浪费资源。一些库缺乏对用户定义调度程序的支持，开发人员求助于更难重用和维护的非官方扩展。我们提出了一种名为ARTful 模型的全局调度程序软件设计，以创建用户定义的解决方案，对运行时库进行最少的改动。我们的模型使用基于组件的设计将组件与运行时库和调度策略实现分开。在巧妙的模型描述可移植调度程序库的接口，允许策略在不同的运行时库上运行。我们通过使用工作负载感知调度策略的 ARTful 库实现面向元编程的全局调度库来研究我们的设计引起的开销。我们对来自 OpenMP 和 Charm++ 运行时系统的两种不同策略进行了试验，同时在其原始库上下文之外展示了对策略的评估。我们观察到，我们的便携式调度器有时可以比其原生调度器更快地执行决策，而合成应用程序和分子动力学内核的执行时间开销可以忽略不计。