Le développement de la radio logicielle fait suite à l’évolution rapide du domaine des télécommunications. Les besoins en performance et en dynamicité ont donné naissance à des MPSoC dédiés à la radio logicielle. La spécialisation de ces MPSoC rend cependant leur pro- grammation et leur vérification complexes. Des travaux proposent d’atténuer cette complexité par l’utilisation de paradigmes tels que le modèle de calcul flot de données. Parallèlement, le besoin de modèles flexibles et vérifiables a mené au développement de nouveaux modèles flot de données paramétriques. Dans cette thèse, j’étudie la compilation d’applications utilisant un modèle de calcul flot de données paramétrique et ciblant des plateformes de radio logicielle. Après un état de l’art du matériel et logiciel du domaine, je propose un raffinement de l’ordonnancement flot de données, et présente son application à la vérification des tailles mémoires. Ensuite, j’introduis un nouveau format de haut niveau pour définir le graphe et les acteurs flot de données, ainsi que le flot de compilation associé. J’applique ces concepts à la génération de code optimisé pour la plateforme de radio logicielle Magali. La compilation de parties du protocole LTE permet d’évaluer les performances du flot de compilation proposé. / The emergence of software-defined radio follows the rapidly evolving telecommunication domain. The requirements in both performance and dynamicity has engendered software- defined-radio-dedicated MPSoCs. Specialization of these MPSoCs make them difficult to program and verify. Dataflow models of computation have been suggested as a way to mi- tigate this complexity. Moreover, the need for flexible yet verifiable models has led to the development of new parametric dataflow models. In this thesis, I study the compilation of parametric dataflow applications targeting software-defined-radio platforms. After a hardware and software state of the art in this field, I propose a new refinement of dataflow scheduling, and outline its application to buffer size’s verification. Then, I introduce a new high-level format to define dataflow actors and graph, with the associated compilation flow. I apply these concepts to optimised code generation for the Magali software-defined-radio platform. Compilation of parts of the LTE protocol are used to evaluate the performances of the proposed compilation flow.

Video applications are becoming ubiquitous in recent times due to an explosion in the number of devices with video capture and display capabilities. Traditionally, video applications are implemented on a variety of devices with each device targeting a specific application. However, the advances in technology have created a need to support multiple applications from a single device like a smart phone or tablet. Such convergence of applications necessitates support for interoperability among various applications, scalable performance meet the requirements of different applications and a high degree of reconfigurability to accommodate rapid evolution in applications features. In addition, low power consumption requirement is also very stringent for many video applications. The conventional custom hardware implementations of video applications deliver high performance at low power consumption while the recent MPSoC implementations enable high degree of interoperability and are useful to support application evolution. In this thesis, we combine the best features of custom hardware and MPSoC approaches to design a Polymorphic ASIC. A Polymorphic ASIC is an integrated circuit designed to meet the requirements of several applications belonging to a particular domain. A polymorphic ASIC consists of a fabric of computation, storage and communication resources, using which applications are composed dynamically. Although different video applications differ widely in the internal de-tails of operation, at the heart of almost every video application is a video codec (encoder and decoder). The requirements of scalability, high performance and low power consumption are very stringent for video decoding. Therefore this thesis focuses mainly on the architectural design of a Polymorphic ASIC for video decoding. We present an unified software and hardware architecture (USHA) for Polymorphic ASIC. USHA is a tiled architecture which uses loosely coupled processor and hardware tiles that are software programmable and hardware reconfigurable respectively. The distinctive feature of Polymorphic ASIC is the static partitioning of the application and dynamic mapping of ap-plication processes onto the computational tiles. Depending on the application scenarios, a process may be mapped onto one of the hardware or processor tiles. Polymorphic ASIC incor-porates a network–on–chip (NoC) to achieve flexible communication across different tiles. Formulation of a programming framework for Polymorphic ASIC requires an implementation model that captures the structure of video decoder applications as well as the properties of the Polymorphic ASIC architecture. We derive an implementation model based on a combination of parametric polyhedral process networks, stream based functions and windowed dataflow models of computation. The implementation model leads to a process network oriented compilation flow that achieves realization agnostic application partitioning and enables seamless migration across uniprocessor, multi–processor, semi hardware and full hardware configurations of a video decoder. The thesis also presents an application QoS aware scheduler that selects a decoder configuration that best meets the application performance requirements, thereby enabling dynamic performance scaling. The memory hierarchy of Polymorphic ASIC makes use of an application specific cache. Through a combined analysis of miss rate and external memory bandwidth, we show that the degradation in decoder performance due to memory stall cycles depends on the properties of the video being decoded as well as the behavior of the external memory interface. Based on this observation, we present the design of a reconfigurable 2–D cache architecture which can adjust its parameters in accordance with the characteristics of the video stream being decoded. We validate the Polymorphic ASIC using a proof–of–concept implementation on an FPGA. The performance of H.264 decoder on Polymorphic ASIC is evaluated for uniprocessor, multi processor, hardware accelerated and full hardware configurations. The scaling in performance delivered by these configurations shows that the Polymorphic ASIC enables the application to achieve super linear speedups [1]. The experimental results show that different implementations of a H.264 video decoder on the Polymorphic ASIC can deliver performance comparable to a wide spectrum of devices ranging from embedded processor like ARM 9 to MPSoCs like IBM Cell. We also present the energy consumption of various configurations of video decoders on Polymorphic ASIC and an application to configuration mapping aimed at minimizing the overall energy consumption of a Polymorphic ASIC.

Video applications are becoming ubiquitous in recent times due to an explosion in the number of devices with video capture and display capabilities. Traditionally, video applications are implemented on a variety of devices with each device targeting a specific application. However, the advances in technology have created a need to support multiple applications from a single device like a smart phone or tablet. Such convergence of applications necessitates support for interoperability among various applications, scalable performance meet the requirements of different applications and a high degree of reconfigurability to accommodate rapid evolution in applications features. In addition, low power consumption requirement is also very stringent for many video applications. The conventional custom hardware implementations of video applications deliver high performance at low power consumption while the recent MPSoC implementations enable high degree of interoperability and are useful to support application evolution. In this thesis, we combine the best features of custom hardware and MPSoC approaches to design a Polymorphic ASIC. A Polymorphic ASIC is an integrated circuit designed to meet the requirements of several applications belonging to a particular domain. A polymorphic ASIC consists of a fabric of computation, storage and communication resources, using which applications are composed dynamically. Although different video applications differ widely in the internal de-tails of operation, at the heart of almost every video application is a video codec (encoder and decoder). The requirements of scalability, high performance and low power consumption are very stringent for video decoding. Therefore this thesis focuses mainly on the architectural design of a Polymorphic ASIC for video decoding. We present an unified software and hardware architecture (USHA) for Polymorphic ASIC. USHA is a tiled architecture which uses loosely coupled processor and hardware tiles that are software programmable and hardware reconfigurable respectively. The distinctive feature of Polymorphic ASIC is the static partitioning of the application and dynamic mapping of ap-plication processes onto the computational tiles. Depending on the application scenarios, a process may be mapped onto one of the hardware or processor tiles. Polymorphic ASIC incor-porates a network–on–chip (NoC) to achieve flexible communication across different tiles. Formulation of a programming framework for Polymorphic ASIC requires an implementation model that captures the structure of video decoder applications as well as the properties of the Polymorphic ASIC architecture. We derive an implementation model based on a combination of parametric polyhedral process networks, stream based functions and windowed dataflow models of computation. The implementation model leads to a process network oriented compilation flow that achieves realization agnostic application partitioning and enables seamless migration across uniprocessor, multi–processor, semi hardware and full hardware configurations of a video decoder. The thesis also presents an application QoS aware scheduler that selects a decoder configuration that best meets the application performance requirements, thereby enabling dynamic performance scaling. The memory hierarchy of Polymorphic ASIC makes use of an application specific cache. Through a combined analysis of miss rate and external memory bandwidth, we show that the degradation in decoder performance due to memory stall cycles depends on the properties of the video being decoded as well as the behavior of the external memory interface. Based on this observation, we present the design of a reconfigurable 2–D cache architecture which can adjust its parameters in accordance with the characteristics of the video stream being decoded. We validate the Polymorphic ASIC using a proof–of–concept implementation on an FPGA. The performance of H.264 decoder on Polymorphic ASIC is evaluated for uniprocessor, multi processor, hardware accelerated and full hardware configurations. The scaling in performance delivered by these configurations shows that the Polymorphic ASIC enables the application to achieve super linear speedups [1]. The experimental results show that different implementations of a H.264 video decoder on the Polymorphic ASIC can deliver performance comparable to a wide spectrum of devices ranging from embedded processor like ARM 9 to MPSoCs like IBM Cell. We also present the energy consumption of various configurations of video decoders on Polymorphic ASIC and an application to configuration mapping aimed at minimizing the overall energy consumption of a Polymorphic ASIC.

Depuis son introduction en 1982, la carte auto-organisatrice de Kohonen (Self-Organizing Map : SOM) a prouvé ses capacités de classification et visualisation des données multidimensionnelles dans différents domaines d’application. Les implémentations matérielles de la carte SOM, en exploitant le taux de parallélisme élevé de l’algorithme de Kohonen, permettent d’augmenter les performances de ce modèle neuronal souvent au détriment de la flexibilité. D’autre part, la flexibilité est offerte par les implémentations logicielles qui quant à elles ne sont pas adaptées pour les applications temps réel à cause de leurs performances temporelles limitées. Dans cette thèse nous avons proposé une architecture matérielle distribuée, adaptable, flexible et extensible de la carte SOM à base de NoC dédiée pour une implantation matérielle sur FPGA. A base de cette approche, nous avons également proposé une architecture matérielle innovante d’une carte SOM à structure croissante au cours de la phase d’apprentissage / Since its introduction in 1982, Kohonen’s Self-Organizing Map (SOM) showed its ability to classify and visualize multidimensional data in various application fields. Hardware implementations of SOM, by exploiting the inherent parallelism of the Kohonen algorithm, allow to increase the overall performances of this neuronal network, often at the expense of the flexibility. On the other hand, the flexibility is offered by software implementations which on their side are not suited for real-time applications due to the limited time performances. In this thesis we proposed a distributed, adaptable, flexible and scalable hardware architecture of SOM based on Network-on-Chip (NoC) designed for FPGA implementation. Moreover, based on this approach we also proposed a novel hardware architecture of a growing SOM able to evolve its own structure during the learning phase