The trend towards multi-core/many-core architectures is well underway. It is therefore becoming very important to develop software in ways that take 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 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 synchronous parallel task models on multi-core platforms. Our evaluation results indicate that the proposed analysis significantly advances the state-of-the-art in EDF schedulability analysis for synchronous parallel tasks.
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