A benchmark-driven modelling approach for evaluating deployment choices on a multi-core architecture

The complexity of current and emerging architectures provides users with options about how best to use the available resources, but makes predicting performance challenging. In this work a benchmark-driven model is developed for a simple shallow water code on a Cray XE6 system, to explore how deployment choices such as domain decomposition and core affinity affect performance. The resource sharing present in modern multi-core architectures adds various levels of heterogeneity to the system. Shared resources often includes cache, memory, network controllers and in some cases floating point units (as in the AMD Bulldozer), which mean that the access time depends on the mapping of application tasks, and the core's location within the system. Heterogeneity further increases with the use of hardware-accelerators such as GPUs and the Intel Xeon Phi, where many specialist cores are attached to general-purpose cores. This trend for shared resources and non-uniform cores is expected to continue into the exascale era. The complexity of these systems means that various runtime scenarios are possible, and it has been found that under-populating nodes, altering the domain decomposition and non-standard task to core mappings can dramatically alter performance. To find this out, however, is often a process of trial and error. To better inform this process, a performance model was developed for a simple regular grid-based kernel code, shallow. The code comprises two distinct types of work, loop-based array updates and nearest-neighbour halo-exchanges. Separate performance models were developed for each part, both based on a similar methodology. Application specific benchmarks were run to measure performance for different problem sizes under different execution scenarios. These results were then fed into a performance model that derives resource usage for a given deployment scenario, with interpolation between results as necessary.

Multi-Agent Framework for Spatial Load Forecasting

A multi-agent framework for spatial electric load forecasting, especially suited to simulate the different dynamics involved on distribution systems, is presented. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with a corresponding load level, and their relationships with the neighbor zones are represented as development probabilities. With this setting, different kind of agents can be developed to simulate the growth pattern of the loads in distribution systems. This paper presents two different kinds of agents to simulate different situations, presenting some promissory results.

Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.

Collision Detection: Broad Phase Adaptation from Multi-Core to Multi-GPU Architecture

We present in this paper several contributions on the collision detection optimization centered on hardware performance. We focus on the broad phase which is the first step of the collision detection process and propose three new ways of parallelization of the well-known Sweep and Prune algorithm. We first developed a multi-core model takes into account the number of available cores. Multi-core architecture enables us to distribute geometric computations with use of multi-threading. Critical writing section and threads idling have been minimized by introducing new data structures for each thread. Programming with directives, like OpenMP, appears to be a good compromise for code portability. We then proposed a new GPU-based algorithm also based on the "Sweep and Prune" that has been adapted to multi-GPU architectures. Our technique is based on a spatial subdivision method used to distribute computations among GPUs. Results show that significant speed-up can be obtained by passing from 1 to 4 GPUs in a large-scale environment.

Professionalisation of sport federations. A multi-level framework for analysing forms, causes and consequences

Research question: International and national sport federations as well as their member organisations (usually sport clubs) are key actors within the sport system and have a wide range of relationships outside the sport system (e.g. with the state, sponsors, and the media). They are currently facing major challenges such as growing competition in top-level sports, democratisation of sports with “sports for all” and sports as the answer to social problems (integration, education, health, unemployment, etc.). In this context, professionalising sport organisations seems to be an appropriate strategy to face these challenges and solve current problems. We define the professionalisation of sport organisations as an organisational process of transformation leading towards organisational rationalisation, efficiency and business-like management. This has led to a profound organisational change, particularly within sport federations, characterised by the strengthening of institutional management (managerialism) and the implementation of efficiency-based management instruments and paid staff. Research methods: The goal of this article is to review the international literature and establish a global understanding of and theoretical framework for how sport organisations professionalise and what consequences this may have. Results and Findings: Our multi-level approach based on the social theory of action integrates the current concepts for analysing professionalisation in sport federations. We specify the framework for the following research perspectives: (1) forms, (2) causes and (3) consequences, and discuss the reciprocal relations between sport federations and their member organisations in this context. Implications: Finally, we derive general methodological consequences for the investigation of professionalisation processes in sport organisations.

Professionalisation of sport federations – A multi-level framework for analysing forms, causes and consequences

Research question: International and national sport federations as well as their member organisations are key actors within the sport system and have a wide range of relationships outside the sport system (e.g. with the state, sponsors, and the media). They are currently facing major challenges such as growing competition in top-level sports, democratisation of sports with ‘sports for all’ and sports as the answer to social problems. In this context, professionalising sport organisations seems to be an appropriate strategy to face these challenges and current problems. We define the professionalisation of sport organisations as an organisational process of transformation leading towards organisational rationalisation, efficiency and business-like management. This has led to a profound organisational change, particularly within sport federations, characterised by the strengthening of institutional management (managerialism) and the implementation of efficiency-based management instruments and paid staff. Research methods: The goal of this article is to review the current international literature and establish a global understanding of and theoretical framework for analysing why and how sport organisations professionalise and what consequences this may have. Results and findings: Our multi-level approach based on the social theory of action integrates the current concepts for analysing professionalisation in sport federations. We specify the framework for the following research perspectives: (1) forms, (2) causes and (3) consequences, and discuss the reciprocal relations between sport federations and their member organisations in this context. Implications: Finally, we work out a research agenda and derive general methodological consequences for the investigation of professionalisation processes in sport organisations.

Professionalisation of sports federations – A multi-level framework for analysing forms, causes and consequences

Introduction: International and national sports federations as well as their member organisations (usually sports clubs) are key actors within the sports system and have a wide range of relationships outside the sports system (e.g. with the state, sponsors, and the media). They are currently facing major challenges such as growing competition in top-­‐level sports, democratisation of sports with “sports for all” and sports as the answer to social problems (integration, education, health, unemployment, etc.). In this context, professionalising sports organisations seems to be an appropriate strategy to face these challenges and solve current problems. This has led to a profound organisational change, particularly within sports federations, characterised by the strengthening of institutional management (managerialism) and the implementation of efficiency-­‐based management instruments and paid staff. In this context the questions arise how sports organisations professionalise and what consequences this may have. Theoretical framework: The goal of our presentation is to review the international literature and develop an appropriate concept of professionalisation in sport federations. Our multi-­‐level approach based on social theory of action integrates the current concepts and perspectives for analysing professionalisation in sports federations. We specify the framework for the following research perspectives: (1) forms, (2) causes and mechanisms, (3) consequences and (4) dynamics, and discuss the reciprocal relations between sports federations and their member organisations in this context. When analysing these different research perspectives, it is important to select or elaborate appropriate theoretical concepts to match the general multi-­‐level framework Discussion: The elaborated multi-­‐level framework for analysing professionalisation in sports federations is able to integrate most of the existing theoretical concepts and therefore, the broad range of endogenous as well as exogenous factors that might influence the professionalisation of sports organisations. Based on the theoretical framework, we can identify several consequences for the methodological design of studies intending to analyse the different perspectives of professionalisation in sports organisations: Data have to be collected on the different levels. Not only the forms of professionalisation and relevant structures of the organisations should be taken into account but also important characteristics of the environment (macro level) as well as members or member organisations, particularly key actors who might play a crucial role in gaining an understanding of professionalisation processes in sports organisations. In order to carry out a complex organisational research design, it seems necessary to focus on case studies – an approach that has become increasingly important in organisational research. Different strategies and methods of data collection have to be used within the case studies (e.g. interviews with experts within the organisations, questionnaire for selected people in the organisation, document analysis). Therefore, qualitative and quantitative research strategies have to be combined.

A region based approach to background modeling in a wavelet multi-resolution framework

In the field of detection and monitoring of dynamic objects in quasi-static scenes, background subtraction techniques where background is modeled at pixel-level, although showing very significant limitations, are extensively used. In this work we propose a novel approach to background modeling that operates at region-level in a wavelet based multi-resolution framework. Based on a segmentation of the background, characterization is made for each region independently as a mixture of K Gaussian modes, considering the model of the approximation and detail coefficients at the different wavelet decomposition levels. Background region characterization is updated along time, and the detection of elements of interest is carried out computing the distance between background region models and those of each incoming image in the sequence. The inclusion of the context in the modeling scheme through each region characterization makes the model robust, being able to support not only gradual illumination and long-term changes, but also sudden illumination changes and the presence of strong shadows in the scene

Design equations for reinforced concrete members strengthened in shear with external FRP reinforcement formulated in an evolutionary multi-objective framework

Methods for predicting the shear capacity of FRP shear strengthened RC beams assume the traditional approach of superimposing the contribution of the FRP reinforcing to the contributions from the reinforcing steel and the concrete. These methods become the basis for most guides for the design of externally bonded FRP systems for strengthening concrete structures. The variations among them come from the way they account for the effect of basic shear design parameters on shear capacity. This paper presents a simple method for defining improved equations to calculate the shear capacity of reinforced concrete beams externally shear strengthened with FRP. For the first time, the equations are obtained in a multiobjective optimization framework solved by using genetic algorithms, resulting from considering simultaneously the experimental results of beams with and without FRP external reinforcement. The performance of the new proposed equations is compared to the predictions with some of the current shear design guidelines for strengthening concrete structures using FRPs. The proposed procedure is also reformulated as a constrained optimization problem to provide more conservative shear predictions.

Efficient tool path computation using multi-core GPUs

Tool path generation is one of the most complex problems in Computer Aided Manufacturing. Although some efficient strategies have been developed, most of them are only useful for standard machining. However, the algorithms used for tool path computation demand a higher computation performance, which makes the implementation on many existing systems very slow or even impractical. Hardware acceleration is an incremental solution that can be cleanly added to these systems while keeping everything else intact. It is completely transparent to the user. The cost is much lower and the development time is much shorter than replacing the computers by faster ones. This paper presents an optimisation that uses a specific graphic hardware approach using the power of multi-core Graphic Processing Units (GPUs) in order to improve the tool path computation. This improvement is applied on a highly accurate and robust tool path generation algorithm. The paper presents, as a case of study, a fully implemented algorithm used for turning lathe machining of shoe lasts. A comparative study will show the gain achieved in terms of total computing time. The execution time is almost two orders of magnitude faster than modern PCs.

Fiber Bragg grating structures inscribed using 800nm femtosecond laser in single- and multi-core mid-IR glass fibers with their spectral, thermal and strain properties

Single- and multi-core passive and active germanate and tellurite glass fibers represent a new class of fiber host for in-fiber photonics devices and applications in mid-IR wavelength range, which are in increasing demand. Fiber Bragg grating (FBG) structures have been proven as one of the most functional in-fiber devices and have been mass-produced in silicate fibers by UV-inscription for almost countless laser and sensor applications. However, because of the strong UV absorption in germanate and tellurite fibers, FBG structures cannot be produced by UVinscription. In recent years femtosecond (fs) lasers have been developed for laser machining and microstructuring in a variety of glass fibers and planar substrates. A number of papers have been reported on fabrication of FBGs and long-period gratings in optical fibers and also on the photosensitivity mechanism using 800nm fs lasers. In this paper, we demonstrate for the first time the fabrication of FBG structures created in passive and active single- and three-core germanate and tellurite glass fibers by using 800nm fs-inscription and phase mask technique. With a fs peak power intensity in the order of 1011W/cm2, the FBG spectra with 2nd and 3rd order resonances at 1540nm and 1033nm in a single-core germanate glass fiber and 2nd order resonances between ~1694nm and ~1677nm with strengths up to 14dB in all three cores of three-core passive and active tellurite fibers were observed. Thermal and strain properties of the FBGs made in these mid-IR glass fibers were characterized, showing an average temperature responsivity of ~20pm/°C and a strain sensitivity of 1.219±0.003pm/µe.

Fiber Bragg gratings inscribed using 800nm femtosecond laser and a phase mask in singleand multi-core mid-IR glass fibers

For the first time, Fiber Bragg grating (FBG) structures have been inscribed in single-core passive germanate and three-core passive and active tellurite glass fibers using 800nm femtosecond (fs) laser and phase mask technique. With fs peak power intensity in the order of 1011W/cm2, the FBG spectra with 2nd and 3rd order resonances at 1540 and 1033nm in the germanate glass fiber and 2nd order resonances at ~1694 and ~1677nm with strengths up to 14dB in all three cores in the tellurite fiber were observed. Thermal responsivities of the FBGs made in these mid-IR glass fibers were characterized, showing average temperature responsivity ~20pm/°C. Strain responsivities of the FBGs in germanate glass fiber were measured to be 1.219pm/µe.