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Scheduling Challenges in Mixed Critical Real-time Heterogeneous Computing Platforms

机译:混合关键实时异构计算平台中的挑战

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In Dynamic Data-Driven Application Systems (DDDAS), applications must dynamically adapt their behavior in response to objectives and'conditions that change while deployed. Often these applications may be safety critical or tightly resource constrained, with a.need for graceful degradation when introduced to unexpected conditions. This paper begins by motivating and providing a vision for a dynamically adaptable mixed critical computing platform to support DDDAS applications. We then specifically focus on the need for advancements in task models and scheduling algorithms to manage the resources of such a platform. We discuss the short comings of existing task models for capturing important attributes of our envisioned computing platform, and identify challenges that must be addressed when developing scheduling algorithms that act upon our proposed extended task model.
机译:在动态数据驱动应用程序系统(DDDA)中,应用程序必须动态调整其行为,以响应于部署时更改的目标和调节。通常,这些应用程序可能是安全临界或紧密资源受到限制,在引入意外条件时,可以为优雅的劣化。本文通过激励和提供动态适应的混合关键计算平台来支持支持DDDA应用的愿景。然后,我们专门关注任务模型和调度算法中的进步的需求来管理这种平台的资源。我们讨论了现有任务模型的短暂关注,以捕获我们设想的计算平台的重要属性,并确定在开发在我们提出的扩展任务模型的调度算法时必须解决的挑战。

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