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Global EDF Schedulability Analysis for Parallel Tasks on Multi-Core Platforms

机译：针对多核平台上并行任务的全局EDF可调度性分析

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摘要

With the widespread adoption of multi-core architectures, it is becoming more important to develop software in ways that takes advantage of such parallel architectures. This particularly entails a shift in programming paradigms towards fine-grained, thread-parallel computing. Many parallel programming models have been introduced for targeting such intra-task thread-level parallelism. However, most successful results on traditional multi-core real-time scheduling are focused on sequential programming models. For example, thread-level parallelism is not properly captured into the concept of interference, which is key to many schedulability analysis techniques. Thereby, most interference-based analysis techniques are not directly applicable to parallel programming models. Motivated by this, we extend the notion of interference to capture thread-level parallelism more accurately. We then leverage the proposed notion of parallelism-aware interference to derive efficient EDF schedulability tests that are directly applicable to parallel task models, including DAG models, on multi-core platforms, without knowing an optimal schedule. Our evaluation results indicate that the proposed analysis significantly advances the state-of-the-art in global EDF schedulability analysis for parallel tasks. In particular, we identify that our proposed schedulability tests are adaptive to different degrees of thread-level parallelism and scalable to the number of processors, resulting in substantial improvement of schedulability for parallel tasks on multi-core platforms.
机译：随着多核体系结构的广泛采用，以利用这种并行体系结构的方式开发软件变得越来越重要。这尤其需要将编程范式转向细粒度的线程并行计算。已经引入了许多针对此类任务内线程级并行性的并行编程模型。但是，传统的多核实时调度的大多数成功结果都集中在顺序编程模型上。例如，线程级并行性没有正确地包含在干扰的概念中，这是许多可调度性分析技术的关键。因此，大多数基于干扰的分析技术不能直接应用于并行编程模型。因此，我们扩展了干扰的概念，以更准确地捕获线程级并行性。然后，我们利用提出的并行感知干扰概念来推导有效的EDF可调度性测试，该测试可直接应用于多核平台上的并行任务模型（包括DAG模型），而无需知道最佳调度。我们的评估结果表明，所提出的分析大大提高了并行任务的全局EDF可调度性分析的最新水平。尤其是，我们确定我们提出的可调度性测试可适应不同程度的线程级并行性，并且可扩展到处理器数量，从而大大提高了多核平台上并行任务的可调度性。

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