Gestion dynamique du parallélisme dans les architectures multi-cœurs pour applications mobiles

Abstract : The amount of smartphone sales recently surpassed the desktop computer ones. This is mainly due to the smart integration of many functionalities in the same architecture. This is also due to the wide variety of supported applications like augmented reality, video conferencing and video games. The support of these applications is made by heterogeneous computing resources specialized to support each application type thus allowing to meet required performance and power consumption. For example, multimedia applications are accelerated by hardware modules that help video encoding and decoding and video game 3D rendering is accelerated by specialized processors (GPU). However, applications become more and more complicated. As an example, augmented reality requires image processing, 3D rendering and computing the information to display. This complexity often comes with a variation of the computing load, which dynamically changes application performance requirements. When this application is implemented in parallel, the way parallelism is chosen for a specific workload, becomes inefficient for a different one. This leads to a waste in computing resources and our objective is to optimize the usage of all available computing resources at runtime. The selected use case is a graphic rendering pipeline application because it is a dynamic application, which is also widely used in mobile devices. This application has been implemented and parallelized on a multicore architecture simulator. The profiling shows that the dynamicity of the application, the time and the amount of data needed to compute vary. The profiling also shows that the best balance of the parallelism depends on the rendered scene; a dynamic load balancing is therefore required for this application. These studies brought us about defining a system allowing to dynamically adapt the application parallelism depending on a prediction of its computing requirements, which can be performed by monitoring the data exchanges between the application tasks. Then the new parallelism is calculated for each stage by a central controller that manages the whole application. This system has been implemented in a Timed-TLM simulator in order to estimate performance improvements allowed by the dynamic adaptation. An architecture allowing to accelerate mobile applications, such as general-purpose and 3D applications, has been defined and compared to other multicore architectures. The hardware complexity and the performance of the architecture have also been estimated. For an increased complexity lower that 1,5%, we demonstrate performance improvements up to 20% compared with static parallelisms. We also demonstrated the ability to support a variable amount of resources.
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Matthieu Texier. Gestion dynamique du parallélisme dans les architectures multi-cœurs pour applications mobiles. Traitement du signal et de l'image [eess.SP]. Université de Rennes 1, 2014. Français. ⟨tel-01099853⟩

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