A Monitoring System for Runtime Adaptations of Streaming Applications

International audienceStreaming languages are adequate for expressing many applications quite naturally and have been proven to be a good approach for taking advantage of the intrinsic parallelism of modern CPU architectures. While numerous works focus on improving the throughput of streaming programs, we rather focus on satisfying quality-of-service requirements of streaming applications executed alongside non-streaming processes. We monitor synchronous dataflow (SDF) programs at runtime both at the application and system levels in order to identify violations of quality-of-service requirements. Our monitoring requires the programmer to provide the expected throughput of its application (e.g 25 frames per second for a video decoder), then takes full benefit from the compilation of the SDF graph to detect bottlenecks in this graph and identify causes among processor or memory overloading. It can then be used to perform dynamic adaptations of the applications in order to optimize the use of computing and memory resources

Ordonnancement d'applications à flux de données pour les MPSoC embarqués hybrides comprenant des unités de calcul programmables et des accélérateurs matériels

Although numerous electronic devices are nowadays able to play video contents in real time and offer high-quality reproduction, video decoding in embedded systems has not become a trivial process yet. As a mater of fact, recent codecs such as H.264 and HEVC exhibit such a complexity that resorting to mixed sofware-hardware architecture is almost unavoidable. However, programming efficiently this kind of platforms is well-known to be tricky. This thesis addresses the issue of developing streaming applications for hybrid embedded targets and executing them efficiently, and proposes several contributions. The first one is an extension of the classical list-scheduling heuristics to take memory constraints into account. Te second one is a datafow execution model compatible with most existing models and with a large set of hardware platforms, as well as a dynamic scheduler. Lastly, numerous developments have been carried out on a real-world architecture from STMicroelectronics so as to demonstrate the feasibility of the approach.Bien que de nombreux appareils numériques soient aujourd'hui capables de lire des contenus vidéo en temps réel et d'offrir une restitution de grande qualité, le décodage vidéo dans les systèmes embarqués n'en est pas pour autant devenu une opération anodine. En effet, les codecs récents tels que H.264 et HEVC sont d'une complexité telle que le recours à des architectures mixtes logiciel/matériel est presque incontournable. Or les plateformes de ce type sont notoirement difficiles à programmer efficacement. Cette thèse relève le défi du développement d'applications à flux de données pour les cibles embarquées hybrides et de leur exécution efficace, et propose plusieurs contributions. La première est une extension des heuristiques d'ordonnancement de liste pour tenir compte des contraintes mémorielles. La seconde est un modèle d'exécution à flot de données compatible avec la plupart des modèles existants et avec une large classe de plateformes matérielles, ainsi qu'un ordonnanceur dynamique. Enfin, de nombreux développements ont été menés sur une architecture réelle de STMicroelectronics pour démontrer la faisabilité de l'approche

Resource Allocation for Software Pipelines in Many-core Systems

Many-core systems integrate a growing number of cores on a single chip and are expected to integrate hundreds and even thousands of cores soon. Despite their massive processing power, it is crucial to employ their resources efficiently to benefit from parallel processing. This dissertation tackles a major challenge, resource allocation, for complex, memory-intensive applications. The proposed methods allow to significantly improve the performance over the state of the art in many scenarios