QPACE 2 and Domain Decomposition on the Intel Xeon Phi

We give an overview of QPACE 2, which is a custom-designed supercomputer based on Intel Xeon Phi processors, developed in a collaboration of Regensburg University and Eurotech. We give some general recommendations for how to write high-performance code for the Xeon Phi and then discuss our implementation of a domain-decomposition-based solver and present a number of benchmarks.Comment: plenary talk at Lattice 2014, to appear in the conference proceedings PoS(LATTICE2014), 15 pages, 9 figure

Performance assessment in water supply and distribution

Abstract unavailable please refer to PD

Konsistente Feature Modell gesteuerte Softwareproduktlinien Evolution

SPLs are an approach to manage families of closely related software systems in terms of configurable functionality. A feature model captures common and variable functionalities of an SPL on a conceptual level in terms of features. Reusable artifacts, such as code, documentation, or tests are related to features using a feature-artifact mapping. A product of an SPL can be derived by selecting features in a configuration. Over the course of time, SPLs and their artifacts are subject to change. As SPLs are particularly complex, their evolution is a challenging task. Consequently, SPL evolution must be thoroughly planned well in advance. However, plans typically do not turn out as expected and, thus, replanning is required. Feature models lean themselves for driving SPL evolution. However, replanning of feature-model evolution can lead to inconsistencies and feature-model anomalies may be introduced during evolution. Along with feature-model evolution, other SPL artifacts, especially configurations, need to consistently evolve. The work of this thesis provides remedy to the aforementioned challenges by presenting an approach for consistent evolution of SPLs. The main contributions of this thesis can be distinguished into three key areas: planning and replanning feature-model evolution, analyzing feature-model evolution, and consistent SPL artifact evolution. As a starting point for SPL evolution, we introduce Temporal Feature Models (TFMs) that allow capturing the entire evolution timeline of a feature model in one artifact, i.e., past history, present changes, and planned evolution steps. We provide an execution semantics of feature-model evolution operations that guarantees consistency of feature-model evolution timelines. To keep feature models free from anomalies, we introduce analyses to detect anomalies in feature-model evolution timelines and explain these anomalies in terms of their causing evolution operations. To enable consistent SPL artifact evolution, we generalize the concept of modeling evolution timelines in TFMs to be applicable for any modeling language. Moreover, we provide a methodology that enables involved engineers to define and use guidance for configuration evolution.Softwareproduktlinien (SPLs) ermöglichen es, konfigurierbare Funktionalität von eng verwandten Softwaresystemen zu verwalten. In einem Feature Modell werden gemeinsame und variable Funktionalitäten einer SPL auf Basis abstrakter Features modelliert. Wiederverwendbare Artefakte werden in einem Feature-Artefakt Mapping Features zugeordnet. Ein Produkt einer SPL kann abgeleitet werden, indem Features in einer Konfiguration ausgewählt werden. Im Laufe der Zeit müssen sich SPLs und deren Artefakte verändern. Da SPLs ganze Softwarefamilien modellieren, ist deren Evolution eine besonders herausfordernde Aufgabe, die gründlich im Voraus geplant werden muss. Feature Modelle eignen sich besonders als Planungsmittel einer SPL. Umplanung von Feature Modell Evolution kann jedoch zu Inkonsistenzen führen und Feature Modell Anomalien können im Zuge der Evolution eingeführt werden. Im Anschluss an die Feature Modell Evolution muss die Evolution anderer SPL Artefakte, insbesondere Konfigurationen, konsistent modelliert werden. In dieser Arbeit wird ein Ansatz zur konsistenten Evolution von SPLs vorgestellt, der die zuvor genannten Herausforderungen adressiert. Die Beiträge dieser Arbeit lassen sich in drei Kernbereiche aufteilen: Planung und Umplanung von Feature Modell Evolution, Analyse von Feature Modell Evolution und konsistente Evolution von SPL Artefakten. Temporal Feature Models (TFMs) werden als Startpunkt für SPL Evolution eingeführt. In einem TFM wird die gesamte Evolutionszeitlinie eines Feature Modells in einem Artefakt abgebildet, was sowohl vergangene Änderungen, den aktuellen Zustand, als auch geplante Änderungen beinhaltet. Auf Basis einer Ausführungssemantik wird die Konsistenz von Feature Modell Evolutionszeitlinien sichergestellt. Um Feature Modelle frei von Anomalien zu halten, werden Analysen eingeführt, welche die gesamte Evolutionszeitlinie eines Feature Modells auf Anomalien untersucht und diese mit verursachenden Evolutionsoperationen erklärt. Das Konzept zur Modellierung von Feature Modell Evolutionszeitlinien aus TFMs wird verallgemeinert, um die gesamte Evolution von Modellen beliebiger Modellierungssprachen spezifizieren zu können. Des Weiteren wird eine Methodik vorgestellt, die beteiligten Ingenieuren eine geführte Evolution von Konfigurationen ermöglicht

L’amélioration du processus d’évaluation d’entreprise par la mise en exergue de la valeur financière du capital humain

La problématique managériale à la base de la thèse porte sur l’évaluation financière du capital humain. Plus précisément, la recherche s’intéresse à l’identification et la valorisation des facteurs créateurs de valeur en lien avec le capital humain en contexte d’évaluation d’entreprise. En respect du positionnement méthodologique de cette recherche exploratoire, s’inscrivant dans le paradigme de la théorie enracinée, des entrevues semi dirigées ont permis la collecte de données auprès de 43 professionnels de l’évaluation répartis en trois profils (cabinet comptable, développement local et capital investissement). Les principaux résultats émanant de la recherche résident d’abord dans la modélisation des processus d’évaluation suivis par chacun des profils de répondants, dans lesquels les étapes traitant du capital humain sont identifiées. De plus, les caractéristiques liées au capital humain pouvant influencer le risque d’un projet et/ou la décision d’investir dans celui-ci sont également ciblées et définies, et ce, pour chacun des profils de répondants. En somme, les résultats de la recherche démontrent qu’une importance prépondérante est accordée à l’entrepreneur et/ou aux membres de l’équipe de direction lors de l’évaluation d’une entreprise, ce que la théorie ne laissait pas réellement transparaître. Aussi, malgré l’absence de normes formelles d’évaluation financière du capital humain, les répondants d’un même profil adoptent des façons de faire identiques en ce qui a trait à la prise en considération de l’impact du capital humain sur la détermination de la valeur d’une entreprise. Finalement, l’originalité de cette recherche réside dans la mise en commun de deux champs de recherche jusqu’à présent isolés l’un de l’autre, soit l’évaluation d’entreprise et les facteurs de création de valeur liés au capital humain.Abstract: The managerial problem at the basis of the thesis deals with the financial evaluation of the human capital. More specifically, the research focuses on identifying and assessing value-creating factors linked to human capital in a business valuation context. In compliance with the methodological positioning of this exploratory research, consistent with the grounded theory paradigm, semi-structured interviews helped to collect data from 43 evaluation professionals split into three profiles (accounting firm, local development and private equity). The main results stemming from the research focus on evaluation process mapping followed by each respondent’s profile in which the steps dealing with human capital are identified. Furthermore, the characteristics linked to human capital that can influence the risk of a project and/or the decision to invest in it are also targeted and defined, for each respondent’s profile. All in all, the research results show that paramount importance is given to the business owner and/or members of the management team during a business valuation, which the theory failed to really show. Also, despite the absence of formal standards for the financial evaluation of human capital, respondents of the same profile adopt identical methods when it comes to considering the impact of human capital on the determination of the value of a business. Lastly, the originality of this research lies in the pooling of two research fields that had been isolated from one another thus far, namely business valuation and value-creating factors linked to human capital

Computing resources sensitive parallelization of neural neworks for large scale diabetes data modelling, diagnosis and prediction

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Diabetes has become one of the most severe deceases due to an increasing number of diabetes patients globally. A large amount of digital data on diabetes has been collected through various channels. How to utilize these data sets to help doctors to make a decision on diagnosis, treatment and prediction of diabetic patients poses many challenges to the research community. The thesis investigates mathematical models with a focus on neural networks for large scale diabetes data modelling and analysis by utilizing modern computing technologies such as grid computing and cloud computing. These computing technologies provide users with an inexpensive way to have access to extensive computing resources over the Internet for solving data and computationally intensive problems. This thesis evaluates the performance of seven representative machine learning techniques in classification of diabetes data and the results show that neural network produces the best accuracy in classification but incurs high overhead in data training. As a result, the thesis develops MRNN, a parallel neural network model based on the MapReduce programming model which has become an enabling technology in support of data intensive applications in the clouds. By partitioning the diabetic data set into a number of equally sized data blocks, the workload in training is distributed among a number of computing nodes for speedup in data training. MRNN is first evaluated in small scale experimental environments using 12 mappers and subsequently is evaluated in large scale simulated environments using up to 1000 mappers. Both the experimental and simulations results have shown the effectiveness of MRNN in classification, and its high scalability in data training. MapReduce does not have a sophisticated job scheduling scheme for heterogonous computing environments in which the computing nodes may have varied computing capabilities. For this purpose, this thesis develops a load balancing scheme based on genetic algorithms with an aim to balance the training workload among heterogeneous computing nodes. The nodes with more computing capacities will receive more MapReduce jobs for execution. Divisible load theory is employed to guide the evolutionary process of the genetic algorithm with an aim to achieve fast convergence. The proposed load balancing scheme is evaluated in large scale simulated MapReduce environments with varied levels of heterogeneity using different sizes of data sets. All the results show that the genetic algorithm based load balancing scheme significantly reduce the makespan in job execution in comparison with the time consumed without load balancing.This work is funded by the EPSRC and China Market Association