Software Code Generation for the RVC-CAL Language

International audienceThe MPEG Reconfigurable Video Coding (RVC) framework is a new standard under development by MPEG that aims at providing a unified high-level specification of current and future MPEG video coding technologies using dataflow models. In this framework, a decoder is built as a configuration of video coding modules taken from the standard MPEG toolbox library or proprietary libraries. The elements of the library are specified by a textual description that expresses the I/O behavior of each module and by a reference software written using a subset of the CAL Actor Language named RVC-CAL. A decoder configuration is written in an XML dialect by connecting a set of CAL modules. Code generators are fundamental supports that enable the direct transformation of a high level specification to efficient hardware and software implementations. This paper presents a synthesis tool that from a CAL dataflow program generates C code and an associated SystemC model. The generated code is validated against the original CAL description simulated using the Open Dataflow environment. Experimental results of the translation of two descriptions of an MPEG-4 Simple Profile decoder with different granularities are shown and discussed

Application specific dataflow machine construction for programming FPGAs via Lucent

Field Programmable Gate Arrays (FPGAs) have the potential to accelerate specific HPC codes. However even with the advent of High Level Synthesis (HLS), which enables FPGA programmers to write code in C or C++, programming such devices still requires considerable expertise. Much of this is due to the fact that these architectures are founded on dataflow rather than the Von Neumann abstraction of CPUs or GPUs. Thus programming FPGAs via imperative languages is not optimal and can result in very significant performance differences between the first and final versions of algorithms on dataflow architectures with the steps in between often not obvious and requiring considerable expertise. In this position paper we argue that languages built upon dataflow principals should be exploited to enable fast by construction codes for FPGAs, and this is akin to the programmer adopting the abstraction of developing a bespoke dataflow machine specialised for their application. It is our belief that much can be learnt from the generation of dataflow languages that gained popularity in the 1970s and 1980s around programming general purpose dataflow machines, and we introduce Lucent which is a modern derivative of Lucid, and used as a vehicle to explore this hypothesis. The idea behind Lucent is to provide high programmer productivity and performance for FPGAs by giving developers the most suitable language level abstractions. The focus of Lucent is very much to support the acceleration of HPC kernels, rather than the embedded electronics and circuit level, and we provide a brief overview of the language driven by examples.Comment: Accepted at the LATTE (Languages, Tools, and Techniques for Accelerator Design) ASPLOS worksho

MPEG Reconfigurable Video Coding

WOS - ISBN: 978-1-4419-6344-4The currentmonolithic and lengthy scheme behind the standardization and the design of new video coding standards is becoming inappropriate to satisfy the dynamism and changing needs of the video coding community. Such a scheme and specification formalism do not enable designers to exploit the clear commonalities between the different codecs, neither at the level of the specification nor at the level of the implementation. Such a problem is one of the main reasons for the typical long time interval elapsing between the time a new idea is validated until it is implemented in consumer products as part of a worldwide standard. The analysis of this problem originated a new standard initiative within the ISO/IEC MPEG committee, called Reconfigurable Video Coding (RVC). The main idea is to develop a video coding standard that overcomes many shortcomings of the current standardization and specification process by updating and progressively incrementing a modular library of components. As the name implies, flexibility and reconfigurability are new attractive features of the RVC standard. The RVC framework is based on the usage of a new actor/dataflow oriented language called CAL for the specification of the standard library and the instantiation of the RVC decoder model. CAL dataflow models expose the intrinsic concurrency of the algorithms by employing the notions of actor programming and dataflow. This chapter gives an overview of the concepts and technologies building the standard RVC framework and the non standard tools supporting the RVC model from the instantiation and simulation of the CAL model to the software and/or hardware code synthesis

Dataflow Program Analysis and Refactoring Techniques for Design Space Exploration: MPEG-4 AVC/H.264 Decoder Implementation Case Study

This paper presents a methodology to perform design space exploration of complex signal processing systems implemented using the CAL dataflow language. In the course of space exploration, critical path in dataflow programs is first presented, and then analyzed using a new strategy for computational load reduction. These techniques, together with detecting design bottlenecks, point to the most efficient optimization directions in a complex network. Following these analysis, several new refactoring techniques are introduced and applied on the dataflow program in order to obtain feasible design points in the exploration space. For a MPEG-4 AVC/H.264 decoder software and hardware implementation, the multi-dimensional space can be explored effectively for throughput, resource, and frequency, with real-time decoding range from QCIF to HD resolutions

Implementación de una Support Vector Machine en RVC – CAL para imágenes hiperespectrales

El análisis de imágenes hiperespectrales permite obtener información con una gran resolución espectral: cientos de bandas repartidas desde el espectro infrarrojo hasta el ultravioleta. El uso de dichas imágenes está teniendo un gran impacto en el campo de la medicina y, en concreto, destaca su utilización en la detección de distintos tipos de cáncer. Dentro de este campo, uno de los principales problemas que existen actualmente es el análisis de dichas imágenes en tiempo real ya que, debido al gran volumen de datos que componen estas imágenes, la capacidad de cómputo requerida es muy elevada. Una de las principales líneas de investigación acerca de la reducción de dicho tiempo de procesado se basa en la idea de repartir su análisis en diversos núcleos trabajando en paralelo. En relación a esta línea de investigación, en el presente trabajo se desarrolla una librería para el lenguaje RVC – CAL – lenguaje que está especialmente pensado para aplicaciones multimedia y que permite realizar la paralelización de una manera intuitiva – donde se recogen las funciones necesarias para implementar el clasificador conocido como Support Vector Machine – SVM. Cabe mencionar que este trabajo complementa el realizado en [1] y [2] donde se desarrollaron las funciones necesarias para implementar una cadena de procesado que utiliza el método unmixing para procesar la imagen hiperespectral. En concreto, este trabajo se encuentra dividido en varias partes. La primera de ellas expone razonadamente los motivos que han llevado a comenzar este Trabajo de Investigación y los objetivos que se pretenden conseguir con él. Tras esto, se hace un amplio estudio del estado del arte actual y, en él, se explican tanto las imágenes hiperespectrales como sus métodos de procesado y, en concreto, se detallará el método que utiliza el clasificador SVM. Una vez expuesta la base teórica, nos centraremos en la explicación del método seguido para convertir una versión en Matlab del clasificador SVM optimizado para analizar imágenes hiperespectrales; un punto importante en este apartado es que se desarrolla la versión secuencial del algoritmo y se asientan las bases para una futura paralelización del clasificador. Tras explicar el método utilizado, se exponen los resultados obtenidos primero comparando ambas versiones y, posteriormente, analizando por etapas la versión adaptada al lenguaje RVC – CAL. Por último, se aportan una serie de conclusiones obtenidas tras analizar las dos versiones del clasificador SVM en cuanto a bondad de resultados y tiempos de procesado y se proponen una serie de posibles líneas de actuación futuras relacionadas con dichos resultados. ABSTRACT. Hyperspectral imaging allows us to collect high resolution spectral information: hundred of bands covering from infrared to ultraviolet spectrum. These images have had strong repercussions in the medical field; in particular, we must highlight its use in cancer detection. In this field, the main problem we have to deal with is the real time analysis, because these images have a great data volume and they require a high computational power. One of the main research lines that deals with this problem is related with the analysis of these images using several cores working at the same time. According to this investigation line, this document describes the development of a RVC – CAL library – this language has been widely used for working with multimedia applications and allows an optimized system parallelization –, which joins all the functions needed to implement the Support Vector Machine – SVM - classifier. This research complements the research conducted in [1] and [2] where the necessary functions to implement the unmixing method to analyze hyperspectral images were developed. The document is divided in several chapters. The first of them introduces the motivation of the Master Thesis and the main objectives to achieve. After that, we study the state of the art of some technologies related with this work, like hyperspectral images, their processing methods and, concretely, the SVM classifier. Once we have exposed the theoretical bases, we will explain the followed methodology to translate a Matlab version of the SVM classifier optimized to process an hyperspectral image to RVC – CAL language; one of the most important issues in this chapter is that a sequential implementation is developed and the bases of a future parallelization of the SVM classifier are set. At this point, we will expose the results obtained in the comparative between versions and then, the results of the different steps that compose the SVM in its RVC – CAL version. Finally, we will extract some conclusions related with algorithm behavior and time processing. In the same way, we propose some future research lines according to the results obtained in this document

Generación de una librería RVC – CAL para la etapa de determinación de endmembers en el proceso de análisis de imágenes hiperespectrales

El análisis de imágenes hiperespectrales permite obtener información con una gran resolución espectral: cientos de bandas repartidas desde el espectro infrarrojo hasta el ultravioleta. El uso de dichas imágenes está teniendo un gran impacto en el campo de la medicina y, en concreto, destaca su utilización en la detección de distintos tipos de cáncer. Dentro de este campo, uno de los principales problemas que existen actualmente es el análisis de dichas imágenes en tiempo real ya que, debido al gran volumen de datos que componen estas imágenes, la capacidad de cómputo requerida es muy elevada. Una de las principales líneas de investigación acerca de la reducción de dicho tiempo de procesado se basa en la idea de repartir su análisis en diversos núcleos trabajando en paralelo. En relación a esta línea de investigación, en el presente trabajo se desarrolla una librería para el lenguaje RVC – CAL – lenguaje que está especialmente pensado para aplicaciones multimedia y que permite realizar la paralelización de una manera intuitiva – donde se recogen las funciones necesarias para implementar dos de las cuatro fases propias del procesado espectral: reducción dimensional y extracción de endmembers. Cabe mencionar que este trabajo se complementa con el realizado por Raquel Lazcano en su Proyecto Fin de Grado, donde se desarrollan las funciones necesarias para completar las otras dos fases necesarias en la cadena de desmezclado. En concreto, este trabajo se encuentra dividido en varias partes. La primera de ellas expone razonadamente los motivos que han llevado a comenzar este Proyecto Fin de Grado y los objetivos que se pretenden conseguir con él. Tras esto, se hace un amplio estudio del estado del arte actual y, en él, se explican tanto las imágenes hiperespectrales como los medios y las plataformas que servirán para realizar la división en núcleos y detectar las distintas problemáticas con las que nos podamos encontrar al realizar dicha división. Una vez expuesta la base teórica, nos centraremos en la explicación del método seguido para componer la cadena de desmezclado y generar la librería; un punto importante en este apartado es la utilización de librerías especializadas en operaciones matriciales complejas, implementadas en C++. Tras explicar el método utilizado, se exponen los resultados obtenidos primero por etapas y, posteriormente, con la cadena de procesado completa, implementada en uno o varios núcleos. Por último, se aportan una serie de conclusiones obtenidas tras analizar los distintos algoritmos en cuanto a bondad de resultados, tiempos de procesado y consumo de recursos y se proponen una serie de posibles líneas de actuación futuras relacionadas con dichos resultados. ABSTRACT. Hyperspectral imaging allows us to collect high resolution spectral information: hundred of bands covering from infrared to ultraviolet spectrum. These images have had strong repercussions in the medical field; in particular, we must highlight its use in cancer detection. In this field, the main problem we have to deal with is the real time analysis, because these images have a great data volume and they require a high computational power. One of the main research lines that deals with this problem is related with the analysis of these images using several cores working at the same time. According to this investigation line, this document describes the development of a RVC – CAL library – this language has been widely used for working with multimedia applications and allows an optimized system parallelization –, which joins all the functions needed to implement two of the four stages of the hyperspectral imaging processing chain: dimensionality reduction and endmember extraction. This research is complemented with the research conducted by Raquel Lazcano in her Diploma Project, where she studies the other two stages of the processing chain. The document is divided in several chapters. The first of them introduces the motivation of the Diploma Project and the main objectives to achieve. After that, we study the state of the art of some technologies related with this work, like hyperspectral images and the software and hardware that we will use to parallelize the system and to analyze its performance. Once we have exposed the theoretical bases, we will explain the followed methodology to compose the processing chain and to generate the library; one of the most important issues in this chapter is the use of some C++ libraries specialized in complex matrix operations. At this point, we will expose the results obtained in the individual stage analysis and then, the results of the full processing chain implemented in one or several cores. Finally, we will extract some conclusions related with algorithm behavior, time processing and system performance. In the same way, we propose some future research lines according to the results obtained in this documen

Machine virtuelle universelle pour codage vidéo reconfigurable

Cette thèse propose un nouveau paradigme de représentation d applications pour les machines virtuelles, capable d abstraire l architecture des systèmes informatiques. Les machines virtuelles actuelles reposent sur un modèle unique de représentation d application qui abstrait les instructions des machines et sur un modèle d exécution qui traduit le fonctionnement de ces instructions vers les machines cibles. S ils sont capables de rendre les applications portables sur une vaste gamme de systèmes, ces deux modèles ne permettent pas en revanche d exprimer la concurrence sur les instructions. Or, celle-ci est indispensable pour optimiser le traitement des applications selon les ressources disponibles de la plate-forme cible. Nous avons tout d abord développé une représentation universelle d applications pour machine virtuelle fondée sur la modélisation par graphe flux de données. Une application est ainsi modélisée par un graphe orienté dont les sommets sont des unités de calcul (les acteurs) et dont les arcs représentent le flux de données passant au travers de ces sommets. Chaque unité de calcul peut être traitée indépendamment des autres sur des ressources distinctes. La concurrence sur les instructions dans l application est alors explicite. Exploiter ce nouveau formalisme de description d'applications nécessite de modifier les règles de programmation. A cette fin, nous avons introduit et défini le concept de Représentation Canonique et Minimale d acteur. Il se fonde à la fois sur le langage de programmation orienté acteur CAL et sur les modèles d abstraction d instructions des machines virtuelles existantes. Notre contribution majeure qui intègre les deux nouvelles représentations proposées, est le développement d une Machine Virtuelle Universelle (MVU) dont la spécificité est de gérer les mécanismes d adaptation, d optimisation et d ordonnancement à partir de l infrastructure de compilation Low-Level Virtual Machine. La pertinence de cette MVU est démontrée dans le contexte normatif du codage vidéo reconfigurable (RVC). En effet, MPEG RVC fournit des applications de référence de décodeurs conformes à la norme MPEG-4 partie 2 Simple Profile sous la forme de graphe flux de données. L une des applications de cette thèse est la modélisation par graphe flux de données d un décodeur conforme à la norme MPEG-4 partie 10 Constrained Baseline Profile qui est deux fois plus complexe que les applications de référence MPEG RVC. Les résultats expérimentaux montrent un gain en performance en exécution de deux pour des plates-formes dotées de deux cœurs par rapport à une exécution mono-cœur. Les optimisations développées aboutissent à un gain de 25% sur ces performances pour des temps de compilation diminués de moitié. Les travaux effectués démontrent le caractère opérationnel et universel de cette norme dont le cadre d utilisation dépasse le domaine vidéo pour s appliquer à d autres domaine de traitement du signal (3D, son, photo )This thesis proposes a new paradigm that abstracts the architecture of computer systems for representing virtual machines applications. Current applications are based on abstraction of machine s instructions and on an execution model that reflects operations of these instructions on the target machine. While these two models are efficient to make applications portable across a wide range of systems, they do not express concurrency between instructions. Expressing concurrency is yet essential to optimize processing of application as the number of processing units is increasing in computer systems. We first develop a universal representation of applications for virtual machines based on dataflow graph modeling. Thus, an application is modeled by a directed graph where vertices are computation units (the actors) and edges represent the flow of data between vertices. Each processing units can be treated apart independently on separate resources. Concurrency in the instructions is then made explicitly. Exploit this new description formalism of applications requires a change in programming rules. To that purpose, we introduce and define a Minimal and Canonical Representation of actors. It is both based on actor-oriented programming and on instructions abstraction used in existing Virtual Machines. Our major contribution, which incorporates the two new representations proposed, is the development of a Universal Virtual Machine (UVM) for managing specific mechanisms of adaptation, optimization and scheduling based on the Low-Level Virtual Machine (LLVM) infrastructure. The relevance of the MVU is demonstrated on the MPEG Reconfigurable Video Coding standard. In fact, MPEG RVC provides decoder s reference application compliant with the MPEG-4 part 2 Simple Profile in the form of dataflow graph. One application of this thesis is a new dataflow description of a decoder compliant with the MPEG-4 part 10 Constrained Baseline Profile, which is twice as complex as the reference MPEG RVC application. Experimental results show a gain in performance close to double on a two cores compare to a single core execution. Developed optimizations result in a gain on performance of 25% for compile times reduced by half. The work developed demonstrates the operational nature of this standard and offers a universal framework which exceeds the field of video domain (3D, sound, picture...)EVRY-INT (912282302) / SudocSudocFranceF