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Deployment of loop-intensive applications on heterogeneous multiprocessor architectures

Abstract : Cyber-physical systems (CPSs) are distributed computing-intensive systems, that integrate a wide range of software applications and heterogeneous processing resources, each interacting with the other ones through different communication resources to process a large volume of data sensed from physical, chemical or biological processes. An essential issue in the design stage of these systems is to predict the timing behaviour of software applications and to provide performance guarantee to these applications. In order tackle this issue, efficient static scheduling strategies are required to deploy the computations of software applications on the processing architectures. These scheduling strategies should deal with several constraints, which include the loop-carried dependency constraints between the computational programs as well as the resource and communication constraints of the processing architectures intended to execute these programs. Actually, loops being one of the most time-critical parts of many computing-intensive applications, the optimal timing behaviour and performance of the applications depends on the optimal schedule of loops structures enclosed in the computational programs executed by the applications. Therefore, to provide performance guarantee for the applications, the scheduling strategies should efficiently explore and exploit the parallelism embedded in the repetitive execution patterns of loops while ensuring the respect of resource and communications constraints of the processing architectures of CPSs. Scheduling a loop under resource and communication constraints is a complex problem. To solve it efficiently, heuristics are obviously necessary. However, to design efficient heuristics, it is important to characterize the set of optimal solutions for the scheduling problem. An optimal solution for a scheduling problem is a schedule that achieve an optimal performance goal. In this thesis, we tackle the study of resource-constrained and communication-constrained scheduling of loop-intensive applications on heterogeneous multiprocessor architectures with the goal of optimizing throughput performance for the applications. In order to characterize the set of optimal scheduling solutions and to design efficient scheduling heuristics, we use synchronous dataflow (SDF) model of computation to describe the loop structures specified in the computational programs of software applications and we design software pipelined scheduling strategies based on the structural and mathematical properties of the SDF model.
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Submitted on : Thursday, November 19, 2020 - 6:07:07 PM
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  • HAL Id : tel-03011573, version 1

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Philippe Anicet Glanon. Deployment of loop-intensive applications on heterogeneous multiprocessor architectures. Distributed, Parallel, and Cluster Computing [cs.DC]. Université Paris-Saclay, 2020. English. ⟨NNT : 2020UPASG029⟩. ⟨tel-03011573⟩

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