Scheduling of parallel real-time DAG tasks on multiprocessor systems

Abstract : The interest for multiprocessor systems has recently been increased in industrial applications, and parallel programming API's have been introduced to benefit from new processing capabilities. The use of multiprocessors for real-time systems, whose execution is performed based on certain temporal constraints is now investigated by the industry. Real-time scheduling problem becomes more complex and challenging in that context. In multiprocessor systems, a hard real-time scheduler is responsible for allocating ready jobs to available processors of the systems while respecting their timing parameters.
In this thesis, we study the problem of real-time scheduling of parallel Directed Acyclic Graph (DAG) tasks on homogeneous multiprocessor systems. In this model, a DAG task consists of a set of subtasks that execute under precedence constraints. At all times, the real-time scheduler is responsible for determining how subtasks execute, either sequentially or in parallel, based on the available processors of the system. We propose two DAG scheduling approaches to determine the execution form of DAG tasks. The first approach is the DAG Stretching algorithm, from the Model Transformation approach, which forces DAG tasks to execute as sequentially as possible. The second approach is the Direct Scheduling, which aims at scheduling DAG tasks while respecting their internal dependencies. We provide real-time schedulability analyses for Direct Scheduling at DAG-Level and at Subtask-Level.
Due to the incomparability of DAG scheduling approaches, we use extensive simulations to compare performance of global EDF with global DM scheduling using our simulation tool YARTISS
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Manar Qamhieh. Scheduling of parallel real-time DAG tasks on multiprocessor systems. Computation and Language [cs.CL]. Université Paris-Est, 2015. English. ⟨NNT : 2015PEST1030⟩. ⟨tel-01233408⟩

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