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Efficient scheduling of applications onto cloud FPGAs

Abstract : This thesis has been realized in Télécom Paris and it has been financed by Nokia Bell Labs France. It founds its motivations in the increasing usage of hardware accelerators such as FPGAs and their recent integration in modern cloud data center [1][2]. In some cases, servers and FPGAs are rented to users and the cost is related to the utilization time. Thus, offering a better sharing of FPGA pools would interest all stakeholders, namely cloud providers and users. We focus on scheduling and, in particular, we focus on makespan minimization of applications. The latter are assumed to be composed of several dependent tasks, whose features (i.e., dependencies, execution time, resource requirements, and so on) are known prior to their execution. With respect to the state of the art, we have sought to design an approach which is, at the same time, (i) general, (ii) fast and (iii) of high-quality. Indeed, several related works represent the applications and the architecture through simple models (e.g., the FPGA is often represented only with the amount of reconfigurable logic). We retain that such simple models may lead to unfeasible scheduling. Moreover, the vast majority of them is either based on slow and precise algorithms or on fast heuristics whose quality is far from the optimum. We therefore propose a scheduling solution [3] characterized by a good quality in terms of makespan while keeping the decision time in the order of tens of milliseconds for common applications. The main contributions of the thesis are a modelling proposal for FPGAs, the design of a heuristic which targets the makespan minimization and the evaluation of this heuristic on a synthetic benchmark of pseudo-randomly generated applications. Additionally, we have integrated this method to a model-driven engineering (MDE) tool to better support the early design of embedded systems. Finally, we propose several extensions to extend the approach to different architectures.References:[1] A. M. Caulfield et al., "A cloud-scale acceleration architecture," 2016 49th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), Taipei, 2016, pp. 1-13, doi: 10.1109/MICRO.2016.7783710[2] Amazon Web Services Elastic Compute Cloud, https://docs.aws.amazon.com/ec2/index.html?nc2=h_ql_doc_ec2[3] Matteo Bertolino, Andrea Enrici, Renaud Pacalet, Ludovic Apvrille. Efficient Scheduling of FPGAs for Cloud Data Center Infrastructures. Euromicro DSD 2020, Aug 2020, Portorož, Slovenia. Proceedings will be published on IEEExplore, paper available on HAL of Télécom Paris: https://hal.telecom-paris.fr/hal-02894662v1
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Matteo Bertolino. Efficient scheduling of applications onto cloud FPGAs. Modeling and Simulation. Institut Polytechnique de Paris, 2021. English. ⟨NNT : 2021IPPAT001⟩. ⟨tel-03276708⟩

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