520 research outputs found

    Programmiersprachen und Rechenkonzepte

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    Die GI-Fachgruppe 2.1.4 "Programmiersprachen und Rechenkonzepte" veranstaltete vom 3. bis 5. Mai 2004 im Physikzentrum Bad Honnef ihren jährlichen Workshop. Dieser Bericht enthält eine Zusammenstellung der Beiträge. Das Treffen diente wie in jedem Jahr gegenseitigem Kennenlernen, der Vertiefung gegenseitiger Kontakte, der Vorstellung neuer Arbeiten und Ergebnisse und vor allem der intensiven Diskussion. Ein breites Spektrum von Beiträgen, von theoretischen Grundlagen über Programmentwicklung, Sprachdesign, Softwaretechnik und Objektorientierung bis hin zur überraschend langen Geschichte der Rechenautomaten seit der Antike bildete ein interessantes und abwechlungsreiches Programm. Unter anderem waren imperative, funktionale und funktional-logische Sprachen, Software/Hardware-Codesign, Semantik, Web-Programmierung und Softwaretechnik, generative Programmierung, Aspekte und formale Testunterstützung Thema. Interessante Beiträge zu diesen und weiteren Themen gaben Anlaß zu Erfahrungsaustausch und Fachgesprächen auch mit den Teilnehmern des zeitgleich im Physikzentrum Bad Honnef stattfindenden Workshops "Reengineering". Allen Teilnehmern möchte ich dafür danken, daß sie mit ihren Vorträgen und konstruktiven Diskussionsbeiträgen zum Gelingen des Workshops beigetragen haben. Dank für die Vielfalt und Qualität der Beiträge gebührt den Autoren. Ein Wort des Dankes gebührt ebenso den Mitarbeitern und der Leitung des Physikzentrums Bad Honnef für die gewohnte angenehme und anregende Atmosphäre und umfassende Betreuung

    High-Level GPU Programming: Domain-Specific Optimization and Inference

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    When writing computer software one is often forced to balance the need for high run-time performance with high programmer productivity. By using a high-level language it is often possible to cut development times, but this typically comes at the cost of reduced run-time performance. Using a lower-level language, programs can be made very efficient but at the cost of increased development time. Real-time computer graphics is an area where there are very high demands on both performance and visual quality. Typically, large portions of such applications are written in lower-level languages and also rely on dedicated hardware, in the form of programmable graphics processing units (GPUs), for handling computationally demanding rendering algorithms. These GPUs are parallel stream processors, specialized towards computer graphics, that have computational performance more than a magnitude higher than corresponding CPUs. This has revolutionized computer graphics and also led to GPUs being used to solve more general numerical problems, such as fluid and physics simulation, protein folding, image processing, and databases. Unfortunately, the highly specialized nature of GPUs has also made them difficult to program. In this dissertation we show that GPUs can be programmed at a higher level, while maintaining performance, compared to current lower-level languages. By constructing a domain-specific language (DSL), which provides appropriate domain-specific abstractions and user-annotations, it is possible to write programs in a more abstract and modular manner. Using knowledge of the domain it is possible for the DSL compiler to generate very efficient code. We show that, by experiment, the performance of our DSLs is equal to that of GPU programs written by hand using current low-level languages. Also, control over the trade-offs between visual quality and performance is retained. In the papers included in this dissertation, we present domain-specific languages targeted at numerical processing and computer graphics, respectively. These DSL have been implemented as embedded languages in Python, a dynamic programming language that provide a rich set of high-level features. In this dissertation we show how these features can be used to facilitate the construction of embedded languages

    The parallel event loop model and runtime: a parallel programming model and runtime system for safe event-based parallel programming

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    Recent trends in programming models for server-side development have shown an increasing popularity of event-based single- threaded programming models based on the combination of dynamic languages such as JavaScript and event-based runtime systems for asynchronous I/O management such as Node.JS. Reasons for the success of such models are the simplicity of the single-threaded event-based programming model as well as the growing popularity of the Cloud as a deployment platform for Web applications. Unfortunately, the popularity of single-threaded models comes at the price of performance and scalability, as single-threaded event-based models present limitations when parallel processing is needed, and traditional approaches to concurrency such as threads and locks don't play well with event-based systems. This dissertation proposes a programming model and a runtime system to overcome such limitations by enabling single-threaded event-based applications with support for speculative parallel execution. The model, called Parallel Event Loop, has the goal of bringing parallel execution to the domain of single-threaded event-based programming without relaxing the main characteristics of the single-threaded model, and therefore providing developers with the impression of a safe, single-threaded, runtime. Rather than supporting only pure single-threaded programming, however, the parallel event loop can also be used to derive safe, high-level, parallel programming models characterized by a strong compatibility with single-threaded runtimes. We describe three distinct implementations of speculative runtimes enabling the parallel execution of event-based applications. The first implementation we describe is a pessimistic runtime system based on locks to implement speculative parallelization. The second and the third implementations are based on two distinct optimistic runtimes using software transactional memory. Each of the implementations supports the parallelization of applications written using an asynchronous single-threaded programming style, and each of them enables applications to benefit from parallel execution

    An Object-Oriented Programming Environment for Parallel Genetic Algorithms

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    This thesis investigates an object-oriented programming environment for building parallel applications based on genetic algorithms (GAs). It describes the design of the Genetic Algorithms Manipulation Environment (GAME), which focuses on three major software development requirements: flexibility, expandability and portability. Flexibility is provided by GAME through a set of libraries containing pre-defined and parameterised components such as genetic operators and algorithms. Expandability is offered by GAME'S object-oriented design. It allows applications, algorithms and genetic operators to be easily modified and adapted to satisfy diverse problem's requirements. Lastly, portability is achieved through the use of the standard C++ language, and by isolating machine and operating system dependencies into low-level modules, which are hidden from the application developer by GAME'S application programming interfaces. The development of GAME is central to the Programming Environment for Applications of PArallel GENetic Algorithms project (PAPAGENA). This is the principal European Community (ESPRIT III) funded parallel genetic algorithms project. It has two main goals: to provide a general-purpose tool kit, supporting the development and analysis of large-scale parallel genetic algorithms (PGAs) applications, and to demonstrate the potential of applying evolutionary computing in diverse problem domains. The research reported in this thesis is divided in two parts: i) the analysis of GA models and the study of existing GA programming environments from an application developer perspective; ii) the description of a general-purpose programming environment designed to help with the development of GA and PGA-based computer programs. The studies carried out in the first part provide the necessary understanding of GAs' structure and operation to outline the requirements for the development of complex computer programs. The second part presents GAME as the result of combining development requirements, relevant features of existing environments and innovative ideas, into a powerful programming environment. The system is described in terms of its abstract data structures and sub-systems that allow the representation of problems independently of any particular GA model. GAME's programming model is also presented as general-purpose object-oriented framework for programming coarse-grained parallel applications. GAME has a modular architecture comprising five modules: the Virtual Machine, the Parallel Execution Module, the Genetic Libraries, the Monitoring Control Module, and the Graphic User Interface. GAME's genetic-oriented abstract data structures, and the Virtual Machine, isolates genetic operators and algorithms from low-level operations such as memory management, exception handling, etc. The Parallel Execution Module supports GAME's object- oriented parallel programming model. It defines an application programming interface and a runtime library that allow the same parallel application, created within the environment, to run on different hardware and operating system platforms. The Genetic Libraries outline a hierarchy of components implemented as parameterised versions of standard and custom genetic operators, algorithms and applications. The Monitoring Control Module supports dynamic control and monitoring of simulations, whereas the Graphic User Interface defines a basic framework and graphic 'widgets' for displaying and entering data. This thesis describes the design philosophy and rationale behind these modules, covering in more detail the Virtual Machine, the Parallel Execution Module and the Genetic Libraries. The assessment discusses the system's ability to satisfy the main requirements of GA and PGA software development, as well as the features that distinguish GAME from other programming environments

    Visual iconic object-oriented programming to advance computer science education and novice programming

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    Learning how to program a computer is difficult for most people. Computer programming is a cognitively challenging, time consuming, labor intensive, and frustrating endeavor. Years of formal study and training are required to learn a programming language\u27s world of algorithms and data structures. Instructions are coded in advance before the computer demonstrates the desired behavior. Seeing all the programming steps and instruction code is complicated. There exists a tremendous gap between the representations the human brain uses when thinking about a problem and the representations used in programming a computer. Often people are much better at dealing with specific, concrete objects than working with abstract ideas. Concrete and specific programming examples and demonstrations can be very useful. When cleverly chosen and properly used, programming examples and demonstrations help people understand the abstract concepts. Programming by example or demonstration attempts to extend these novel ideas to novice programming

    A system for the analysis of musical data

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    The role of music analysis is to enlighten our understanding of a piece of music. The role of musical performance analysis is to help us understand how a performer interprets a piece of music. The current work provides a tool which combines music analysis with performance analysis. By combining music and performance analysis in one system new questions can be asked of a piece of music: how is the structure of a piece reflected in the performance and how can the performance enlighten our understanding of the piece's structure? The current work describes a unified database which can store and present musical score alongside associated performance data and musical analysis. Using a general purpose representation language, Performance Mark-up Language (PML), aspects of performance are recorded and analysed. Data thus acquired from one project is made available to others. Presentation involves high-quality scores suitably annotated with the requested information. Such output is easily and directly accessible to musicians, performance scientists and analysts. We define a set of data structures and operators which can operate on musical pitch and musical time, and use them to form the basis of a query language for a musical database. The database can store musical information (score, gestural data, etc.). Querying the database results in annotations of the musical score. The database is capable of storing musical score information and performance data and cross-referencing them. It is equipped with the necessary primitives to execute music-analytical queries, and highlight notes identified from the score and display performance data alongside the score

    A study of novice programmer performance and programming pedagogy.

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    Identifying and mitigating the difficulties experienced by novice programmers is an active area of research that has embraced a number of research areas. The aim of this research was to perform a holistic study into the causes of poor performance in novice programmers and to develop teaching approaches to mitigate them. A grounded action methodology was adopted to enable the primary concepts of programming cognitive psychology and their relationships to be established, in a systematic and formal manner. To further investigate novice programmer behaviour, two sub-studies were conducted into programming performance and ability. The first sub-study was a novel application of the FP-Tree algorithm to determine if novice programmers demonstrated predictable patterns of behaviour. This was the first study to data mine programming behavioural characteristics rather than the learner’s background information such as age and gender. Using the algorithm, patterns of behaviour were generated and associated with the students’ ability. No patterns of behaviour were identified and it was not possible to predict student results using this method. This suggests that novice programmers demonstrate no set patterns of programming behaviour that can be used determine their ability, although problem solving was found to be an important characteristic. Therefore, there was no evidence that performance could be improved by adopting pedagogies to promote simple changes in programming behaviour beyond the provision of specific problem solving instruction. A second sub-study was conducted using Raven’s Matrices which determined that cognitive psychology, specifically working memory, played an important role in novice programmer ability. The implication was that programming pedagogies must take into consideration the cognitive psychology of programming and the cognitive load imposed on learners. Abstracted Construct Instruction was developed based on these findings and forms a new pedagogy for teaching programming that promotes the recall of abstract patterns while reducing the cognitive demands associated with developing code. Cognitive load is determined by the student’s ability to ignore irrelevant surface features of the written problem and to cross-reference between the problem domain and their mental program model. The former is dealt with by producing tersely written exercises to eliminate distractors, while for the latter the teaching of problem solving should be delayed until the student’s program model is formed. While this does delay the development of problem solving skills, the problem solving abilities of students taught using this pedagogy were found to be comparable with students taught using a more traditional approach. Furthermore, monitoring students’ understanding of these patterns enabled micromanagement of the learning process, and hence explanations were provided for novice behaviour such as difficulties using arrays, inert knowledge and “code thrashing”. For teaching more complex problem solving, scaffolding of practice was investigated through a program framework that could be developed in stages by the students. However, personalising the level of scaffolding required was complicated and found to be difficult to achieve in practice. In both cases, these new teaching approaches evolved as part of a grounded theory study and a clear progression of teaching practice was demonstrated with appropriate evaluation at each stage in accordance with action researc

    Concurrent cell rate simulation of ATM telecommunications network.

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