Generating renderers

Most production renderers developed for the film industry are huge pieces of software that are able to render extremely complex scenes. Unfortunately, they are implemented using the currently available programming models that are not well suited to modern computing hardware like CPUs with vector units or GPUs. Thus, they have to deal with the added complexity of expressing parallelism and using hardware features in those models. Since compilers cannot alone optimize and generate efficient programs for any type of hardware, because of the large optimization spaces and the complexity of the underlying compiler problems, programmers have to rely on compiler-specific hardware intrinsics or write non-portable code. The consequence of these limitations is that programmers resort to writing the same code twice when they need to port their algorithm on a different architecture, and that the code itself becomes difficult to maintain, as algorithmic details are buried under hardware details. Thankfully, there are solutions to this problem, taking the form of Domain-Specific Lan- guages. As their name suggests, these languages are tailored for one domain, and compilers can therefore use domain-specific knowledge to optimize algorithms and choose the best execution policy for a given target hardware. In this thesis, we opt for another way of encoding domain- specific knowledge: We implement a generic, high-level, and declarative rendering and traversal library in a functional language, and later refine it for a target machine by providing partial evaluation annotations. The partial evaluator then specializes the entire renderer according to the available knowledge of the scene: Shaders are specialized when their inputs are known, and in general, all redundant computations are eliminated. Our results show that the generated renderers are faster and more portable than renderers written with state-of-the-art competing libraries, and that in comparison, our rendering library requires less implementation effort.Die meisten in der Filmindustrie zum Einsatz kommenden Renderer sind riesige Softwaresysteme, die in der Lage sind, extrem aufwendige Szenen zu rendern. Leider sind diese mit den aktuell verfügbaren Programmiermodellen implementiert, welche nicht gut geeignet sind für moderne Rechenhardware wie CPUs mit Vektoreinheiten oder GPUs. Deshalb müssen Entwickler sich mit der zusätzlichen Komplexität auseinandersetzen, Parallelismus und Hardwarefunktionen in diesen Programmiermodellen auszudrücken. Da Compiler nicht selbständig optimieren und effiziente Programme für jeglichen Typ Hardware generieren können, wegen des großen Optimierungsraumes und der Komplexität des unterliegenden Kompilierungsproblems, müssen Programmierer auf Compiler-spezifische Hardware-“Intrinsics” zurückgreifen, oder nicht portierbaren Code schreiben. Die Konsequenzen dieser Limitierungen sind, dass Programmierer darauf zurückgreifen den gleichen Code zweimal zu schreiben, wenn sie ihre Algorithmen für eine andere Architektur portieren müssen, und dass der Code selbst schwer zu warten wird, da algorithmische Details unter Hardwaredetails verloren gehen. Glücklicherweise gibt es Lösungen für dieses Problem, in der Form von DSLs. Diese Sprachen sind maßgeschneidert für eine Domäne und Compiler können deshalb Domänenspezifisches Wissen nutzen, um Algorithmen zu optimieren und die beste Ausführungsstrategie für eine gegebene Zielhardware zu wählen. In dieser Dissertation wählen wir einen anderen Weg, Domänenspezifisches Wissen zu enkodieren: Wir implementieren eine generische, high-level und deklarative Rendering- und Traversierungsbibliothek in einer funktionalen Programmiersprache, und verfeinern sie später für eine Zielmaschine durch Bereitstellung von Annotationen für die partielle Auswertung. Der “Partial Evaluator” spezialisiert dann den kompletten Renderer, basierend auf dem verfügbaren Wissen über die Szene: Shader werden spezialisiert, wenn ihre Eingaben bekannt sind, und generell werden alle redundanten Berechnungen eliminiert. Unsere Ergebnisse zeigen, dass die generierten Renderer schneller und portierbarer sind, als Renderer geschrieben mit den aktuellen Techniken konkurrierender Bibliotheken und dass, im Vergleich, unsere Rendering Bibliothek weniger Implementierungsaufwand erfordert.This work was supported by the Federal Ministry of Education and Research (BMBF) as part of the Metacca and ProThOS projects as well as by the Intel Visual Computing Institute (IVCI) and Cluster of Excellence on Multimodal Computing and Interaction (MMCI) at Saarland University. Parts of it were also co-funded by the European Union(EU), as part of the Dreamspace project

Optimized cross-organizational business process monitoring: Design and enactment

Organizations can implement the agility required to survive in the rapidly evolving business landscape by focusing on their core business and engaging in collaborations with other partners. This entails the need for organizations to monitor the behavior of the partners with which they collaborate. The design and enactment of monitoring, in this scenario, must become flexible and adapt as the collaboration evolves. We propose an approach to flexibly design and enact cross-organizational business process monitoring based on Product-Based Workflow Design. Our approach allows organizations to capture monitoring requirements, optimize such requirements, e.g. choosing the monitoring process with lowest cost or highest availability, and enacting the optimal monitoring process through a service-oriented approach. Optimization, in particular, is made efficient by adopting an Ant-colony optimization heuristic. The paper also describes a prototypical implementation of our approach in the ProM framework

Learning how to combine sensory-motor functions into a robust behavior

AbstractThis article describes a system, called Robel, for defining a robot controller that learns from experience very robust ways of performing a high-level task such as “navigate to”. The designer specifies a collection of skills, represented as hierarchical tasks networks, whose primitives are sensory-motor functions. The skills provide different ways of combining these sensory-motor functions to achieve the desired task. The specified skills are assumed to be complementary and to cover different situations. The relationship between control states, defined through a set of task-dependent features, and the appropriate skills for pursuing the task is learned as a finite observable Markov decision process (MDP). This MDP provides a general policy for the task; it is independent of the environment and characterizes the abilities of the robot for the task

A generic approach to the evolution of interaction in ubiquitous systems

This dissertation addresses the challenge of the configuration of modern (ubiquitous, context-sensitive, mobile et al.) interactive systems where it is difficult or impossible to predict (i) the resources available for evolution, (ii) the criteria for judging the success of the evolution, and (iii) the degree to which human judgements must be involved in the evaluation process used to determine the configuration. In this thesis a conceptual model of interactive system configuration over time (known as interaction evolution) is presented which relies upon the follow steps; (i) identification of opportunities for change in a system, (ii) reflection on the available configuration alternatives, (iii) decision-making and (iv) implementation, and finally iteration of the process. This conceptual model underpins the development of a dynamic evolution environment based on a notion of configuration evaluation functions (hereafter referred to as evaluation functions) that provides greater flexibility than current solutions and, when supported by appropriate tools, can provide a richer set of evaluation techniques and features that are difficult or impossible to implement in current systems. Specifically this approach has support for changes to the approach, style or mode of use used for configuration - these features may result in more effective systems, less effort involved to configure them and a greater degree of control may be offered to the user. The contributions of this work include; (i) establishing the the need for configuration evolution through a literature review and a motivating case study experiment, (ii) development of a conceptual process model supporting interaction evolution, (iii) development of a model based on the notion of evaluation functions which is shown to support a wide range of interaction configuration approaches, (iv) a characterisation of the configuration evaluation space, followed by (v) an implementation of these ideas used in (vi) a series of longitudinal technology probes and investigations into the approaches