Development of a Navier-Stokes algorithm for parallel-processing supercomputers

An explicit flow solver, applicable to the hierarchy of model equations ranging from Euler to full Navier-Stokes, is combined with several techniques designed to reduce computational expense. The computational domain consists of local grid refinements embedded in a global coarse mesh, where the locations of these refinements are defined by the physics of the flow. Flow characteristics are also used to determine which set of model equations is appropriate for solution in each region, thereby reducing not only the number of grid points at which the solution must be obtained, but also the computational effort required to get that solution. Acceleration to steady-state is achieved by applying multigrid on each of the subgrids, regardless of the particular model equations being solved. Since each of these components is explicit, advantage can readily be taken of the vector- and parallel-processing capabilities of machines such as the Cray X-MP and Cray-2

The design of a neural network compiler

Computer simulation is a flexible and economical way for rapid prototyping and concept evaluation with Neural Network (NN) models. Increasing research on NNs has led to the development of several simulation programs. Not all simulations have the same scope. Some simulations allow only a fixed network model and some are more general. Designing a simulation program for general purpose NN models has become a current trend nowadays because of its flexibility and efficiency. A proper programming language specifically for NN models is preferred since the existing high-level languages such as C are for NN designers from a strong computer background. The program translations for NN languages come from combinations which are either interpreter and/or compiler. There are also various styles of programming languages such as a procedural, functional, descriptive and object-oriented. The main focus of this thesis is to study the feasibility of using a compiler method for the development of a general-purpose simulator - NEUCOMP that compiles the program written as a list of mathematical specifications of the particular NN model and translates it into a chosen target program. The language supported by NEUCOMP is based on a procedural style. Information regarding the list of mathematical statements required by the NN models are written in the program. The mathematical statements used are represented by scalar, vector and matrix assignments. NEUCOMP translates these expressions into actual program loops. NEUCOMP enables compilation of a simulation program written in the NEUCOMP language for any NN model, contains graphical facilities such as portraying the NN architecture and displaying a graph of the result during training and finally to have a program that can run on a parallel shared memory multi-processor system

Parallel Solver of Large Systems of Linear Inequalities Using Fourier-Motzkin Elimination

Fourier-Motzkin elimination is a computationally expensive but powerful method to solve a system of linear inequalities. These systems arise e.g. in execution order analysis for loop nests or in integer linear programming. This paper focuses on the analysis, design and implementation of a parallel solver for distributed memory for large systems of linear inequalities using the Fourier-Motzkin elimination algorithm. We also measure the speedup of parallel solver and prove that this implementation results in good scalability

A Parallel Branch and Bound Algorithm for the Resource Leveling Problem with Minimal Lags

[EN] The efficient use of resources is a key factor to minimize the cost while meeting time deadlines and quality requirements; this is especially important in construction projects where field operations take fluctuations of resources unproductive and costly. Resource Leveling Problems (RLP) aim to sequence the construction activities that maximize the resource consumption efficiency over time, minimizing the variability. Exact algorithms for the RLP have been proposed throughout the years to offer optimal solutions; however, these problems require a vast computational capability ( combinatorial explosion ) that makes them unpractical. Therefore, alternative heuristic and metaheuristic algorithms have been suggested in the literature to find local optimal solutions, using different libraries to benchmark optimal values; for example, the Project Scheduling Problem LIBrary for minimal lags is still open to be solved to optimality for RLP. To partially fill this gap, the authors propose a Parallel Branch and Bound algorithm for the RLP with minimal lags to solve the RLP with an acceptable computational effort. This way, this research contributes to the body of knowledge of construction project scheduling providing the optimums of 50 problems for the RLP with minimal lags for the first time, allowing future contributors to benchmark their heuristics meth-ods against exact results by obtaining the distance of their solution to the optimal values. Furthermore, for practitioners,the time required to solve this kind of problem is reasonable and practical, considering that unbalanced resources can risk the goals of the construction project.This research was supported by the FAPA program of the Universidad de Los Andes (Colombia). The authors would like to thank the research group of Construction Engineering and Management (INgeco), especially J. S. Rojas-Quintero, and the Department of Systems Engineering at the Universidad de Los Andes. The authors are also grateful to the anonymous reviewers for their valuable and constructive suggestions.Ponz Tienda, JL.; Salcedo-Bernal, A.; Pellicer Armiñana, E. (2017). A Parallel Branch and Bound Algorithm for the Resource Leveling Problem with Minimal Lags. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING. 32:474-498. doi:10.1111/mice.12233S47449832Adeli, H. (2000). High-Performance Computing for Large-Scale Analysis, Optimization, and Control. Journal of Aerospace Engineering, 13(1), 1-10. doi:10.1061/(asce)0893-1321(2000)13:1(1)ADELI, H., & KAMAL, O. (2008). Parallel Structural Analysis Using Threads. Computer-Aided Civil and Infrastructure Engineering, 4(2), 133-147. doi:10.1111/j.1467-8667.1989.tb00015.xAdeli, H., & Kamal, O. (1992). Concurrent analysis of large structures—II. applications. Computers & Structures, 42(3), 425-432. doi:10.1016/0045-7949(92)90038-2Adeli, H., Kamat, M. P., Kulkarni, G., & Vanluchene, R. D. (1993). High‐Performance Computing in Structural Mechanics and Engineering. Journal of Aerospace Engineering, 6(3), 249-267. doi:10.1061/(asce)0893-1321(1993)6:3(249)Adeli, H., & Karim, A. (1997). Scheduling/Cost Optimization and Neural Dynamics Model for Construction. Journal of Construction Engineering and Management, 123(4), 450-458. doi:10.1061/(asce)0733-9364(1997)123:4(450)Adeli, H., & Kumar, S. (1995). Concurrent Structural Optimization on Massively Parallel Supercomputer. Journal of Structural Engineering, 121(11), 1588-1597. doi:10.1061/(asce)0733-9445(1995)121:11(1588)ADELI, H., & VISHNUBHOTLA, P. (2008). Parallel Processing. Computer-Aided Civil and Infrastructure Engineering, 2(3), 257-269. doi:10.1111/j.1467-8667.1987.tb00150.xAdeli, H., & Wu, M. (1998). Regularization Neural Network for Construction Cost Estimation. 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Optimal resource leveling using non-serial dyanamic programming. European Journal of Operational Research, 78(2), 162-177. doi:10.1016/0377-2217(94)90380-8Benjaoran, V., Tabyang, W., & Sooksil, N. (2015). Precedence relationship options for the resource levelling problem using a genetic algorithm. Construction Management and Economics, 33(9), 711-723. doi:10.1080/01446193.2015.1100317Bianco, L., Caramia, M., & Giordani, S. (2016). Resource levelling in project scheduling with generalized precedence relationships and variable execution intensities. OR Spectrum, 38(2), 405-425. doi:10.1007/s00291-016-0435-1Chakroun, I., & Melab, N. (2015). Towards a heterogeneous and adaptive parallel Branch-and-Bound algorithm. Journal of Computer and System Sciences, 81(1), 72-84. doi:10.1016/j.jcss.2014.06.012Christodoulou, S. E., Ellinas, G., & Michaelidou-Kamenou, A. (2010). Minimum Moment Method for Resource Leveling Using Entropy Maximization. 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Multiobjective Optimization of Resource Leveling and Allocation during Construction Scheduling. Journal of Construction Engineering and Management, 137(12), 1080-1088. doi:10.1061/(asce)co.1943-7862.0000368Hiyassat, M. A. S. (2000). Modification of Minimum Moment Approach in Resource Leveling. Journal of Construction Engineering and Management, 126(4), 278-284. doi:10.1061/(asce)0733-9364(2000)126:4(278)Hiyassat, M. A. S. (2001). Applying Modified Minimum Moment Method to Multiple Resource Leveling. Journal of Construction Engineering and Management, 127(3), 192-198. doi:10.1061/(asce)0733-9364(2001)127:3(192)Ismail, M. M., el-raoof, O. abd, & Abd EL-Wahed, W. F. (2014). A Parallel Branch and Bound Algorithm for Solving Large Scale Integer Programming Problems. Applied Mathematics & Information Sciences, 8(4), 1691-1698. doi:10.12785/amis/080425Kolisch, R., & Sprecher, A. (1997). PSPLIB - A project scheduling problem library. European Journal of Operational Research, 96(1), 205-216. doi:10.1016/s0377-2217(96)00170-1Koulinas, G. K., & Anagnostopoulos, K. P. (2013). A new tabu search-based hyper-heuristic algorithm for solving construction leveling problems with limited resource availabilities. Automation in Construction, 31, 169-175. doi:10.1016/j.autcon.2012.11.002Lai, T.-H., & Sahni, S. (1984). Anomalies in parallel branch-and-bound algorithms. Communications of the ACM, 27(6), 594-602. doi:10.1145/358080.358103Leu, S.-S., Yang, C.-H., & Huang, J.-C. (2000). Resource leveling in construction by genetic algorithm-based optimization and its decision support system application. Automation in Construction, 10(1), 27-41. doi:10.1016/s0926-5805(99)00011-4Li, H., Xu, Z., & Demeulemeester, E. (2015). Scheduling Policies for the Stochastic Resource Leveling Problem. 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The Design of Creative Crowdwork – From Tools for Empowerment to Platform Capitalism

The thesis investigates the methods used in the contemporary crowdsourcing of creative crowdwork and in particular the succession of conflicting ideas and concepts that led to the development of dedi- cated, profit-oriented, online platforms after 2005 for the outsourcing of cognitive tasks and creative labour to a large and unspecified group of people via open calls on the internet. It traces the historic trajectory of the notion of the crowd as well as the development of tech- nologies for online collaboration, with a focus on the accompanying narratives in the form of a dis- course analysis. One focus of the thesis is the clash between the narrative of the empowerment of the individual user through digital tools and the reinvention of the concept of the crowd as a way to refer to users of online platforms in their aggregate form. The thesis argues that the revivification of the notion of the crowd is indicative of a power shift that has diminished the agency of the individual user and empowered the commercial platform providers who, in turn, take unfair advantage of the crowdworker. The thesis examines the workings and the rhetoric of these platforms by comparing the way they address the masses today with historic notions of the crowd, formed by authors like Gustave Le Bon, Sigmund Freud and Elias Canetti. Today’s practice of crowdwork is also juxtaposed with older, arguably more humanist, visions of distributed online collaboration, collective intelligence, free soft- ware and commons-based peer production. The study is a history of ideas, taking some of the utopian concepts of early online history as a vantage point from which to view current and, at times, dystopian applications of crowdsourced creative labour online. The goal is to better understand the social mech- anisms employed by the platforms to motivate and control the crowds they gather, and to uncover the parameters that define their structure as well as the scope for their potential redesign. At its core, the thesis offers a comparison of Amazon Mechanical Turk (2005), the most prominent and infamous example for so-called microtasking or cognitive piecework, with the design of platforms for contest-based creative crowdwork, in particular with Jovoto (2007) and 99designs (2008). The crowdsourcing of design work is organised in decidedly differently ways to other forms of digital labour and the question is why should that be so? What does this tell us about changes in the practice and commissioning of design and what are its effects on design as a profession? However, the thesis is not just about the crowdsourcing of design work: it is also about the design of crowdsourcing as a system. It is about the ethics of these human-made, contingent social systems that are promoted as the future of work. The question underlying the entire thesis is: can crowdsourcing be designed in a way that is fair and sustainable to all stakeholders? The analysis is based on an extensive study of literature from Design Studies, Media and Cul- ture Studies, Business Studies and Human-Computer Interaction, combined with participant observa- tion within several crowdsourcing platforms for design and a series of interviews with different stake- holders

Software Coherence in Multiprocessor Memory Systems

Processors are becoming faster and multiprocessor memory interconnection systems are not keeping up. Therefore, it is necessary to have threads and the memory they access as near one another as possible. Typically, this involves putting memory or caches with the processors, which gives rise to the problem of coherence: if one processor writes an address, any other processor reading that address must see the new value. This coherence can be maintained by the hardware or with software intervention. Systems of both types have been built in the past; the hardware-based systems tended to outperform the software ones. However, the ratio of processor to interconnect speed is now so high that the extra overhead of the software systems may no longer be significant. This issue is explored both by implementing a software maintained system and by introducing and using the technique of offline optimal analysis of memory reference traces. It finds that in properly built systems, software maintained coherence can perform comparably to or even better than hardware maintained coherence. The architectural features necessary for efficient software coherence to be profitable include a small page size, a fast trap mechanism, and the ability to execute instructions while remote memory references are outstanding

Automatic parallelisation for a class of URE problems

PhD ThesisThis thesis deals with the methodology and software of automatic parallelisation for numerical supercomputing and supercomputers. Basically, we focus on the problem of Uniform Recurrence Equations (URE) which exists widely in numerical computations. vVepropose a complete methodology of automatic generation of parallel programs for regular array designs. The methodology starts with an introduction of a set of canonical dependencies which generates a general modelling of the various URE problems. Based on these canonical dependencies, partitioning and mapping methods are developed which gives the foundation of the universal design process. Using the theoretical results we propose the structures of parallel programs and eventually generate automatically parallel codes which run correctly and efficiently on transputer array. The achievements presented in this thesis can be regarded as a significant progress in the area of automatic generation of parallel codes and regular (systolic) array design. This methodology is integrated and self-contained, and may be the only practical working package in this area.The Research Committee of University of Newcastle upon Tyne: CVCP Overseas Research Students Awards Scheme

Leveraging human-computer interaction and crowdsourcing for scholarly knowledge graph creation

The number of scholarly publications continues to grow each year, as well as the number of journals and active researchers. Therefore, methods and tools to organize scholarly knowledge are becoming increasingly important. Without such tools, it becomes increasingly difficult to conduct research in an efficient and effective manner. One of the fundamental issues scholarly communication is facing relates to the format in which the knowledge is shared. Scholarly communication relies primarily on narrative document-based formats that are specifically designed for human consumption. Machines cannot easily access and interpret such knowledge, leaving machines unable to provide powerful tools to organize scholarly knowledge effectively. In this thesis, we propose to leverage knowledge graphs to represent, curate, and use scholarly knowledge. The systematic knowledge representation leads to machine-actionable knowledge, which enables machines to process scholarly knowledge with minimal human intervention. To generate and curate the knowledge graph, we propose a machine learning assisted crowdsourcing approach, in particular Natural Language Processing (NLP). Currently, NLP techniques are not able to satisfactorily extract high-quality scholarly knowledge in an autonomous manner. With our proposed approach, we intertwine human and machine intelligence, thus exploiting the strengths of both approaches. First, we discuss structured scholarly knowledge, where we present the Open Research Knowledge Graph (ORKG). Specifically, we focus on the design and development of the ORKG user interface (i.e., the frontend). One of the key challenges is to provide an interface that is powerful enough to create rich knowledge descriptions yet intuitive enough for researchers without a technical background to create such descriptions. The ORKG serves as the technical foundation for the rest of the work. Second, we focus on comparable scholarly knowledge, where we introduce the concept of ORKG comparisons. ORKG comparisons provide machine-actionable overviews of related literature in a tabular form. Also, we present a methodology to leverage existing literature reviews to populate ORKG comparisons via a human-in-the-loop approach. Additionally, we show how ORKG comparisons can be used to form ORKG SmartReviews. The SmartReviews provide dynamic literature reviews in the form of living documents. They are an attempt address the main weaknesses of the current literature review practice and outline how the future of review publishing can look like. Third, we focus designing suitable tasks to generate scholarly knowledge in a crowdsourced setting. We present an intelligent user interface that enables researchers to annotate key sentences in scholarly publications with a set of discourse classes. During this process, researchers are assisted by suggestions coming from NLP tools. In addition, we present an approach to validate NLP-generated statements using microtasks in a crowdsourced setting. With this approach, we lower the barrier to entering data in the ORKG and transform content consumers into content creators. With the work presented, we strive to transform scholarly communication to improve machine-actionability of scholarly knowledge. The approaches and tools are deployed in a production environment. As a result, the majority of the presented approaches and tools are currently in active use by various research communities and already have an impact on scholarly communication.Die Zahl der wissenschaftlichen Veröffentlichungen nimmt jedes Jahr weiter zu, ebenso wie die Zahl der Zeitschriften und der aktiven Forscher. Daher werden Methoden und Werkzeuge zur Organisation von wissenschaftlichem Wissen immer wichtiger. Ohne solche Werkzeuge wird es immer schwieriger, Forschung effizient und effektiv zu betreiben. Eines der grundlegenden Probleme, mit denen die wissenschaftliche Kommunikation konfrontiert ist, betrifft das Format, in dem das Wissen publiziert wird. Die wissenschaftliche Kommunikation beruht in erster Linie auf narrativen, dokumentenbasierten Formaten, die speziell für Experten konzipiert sind. Maschinen können auf dieses Wissen nicht ohne weiteres zugreifen und es interpretieren, so dass Maschinen nicht in der Lage sind, leistungsfähige Werkzeuge zur effektiven Organisation von wissenschaftlichem Wissen bereitzustellen. In dieser Arbeit schlagen wir vor, Wissensgraphen zu nutzen, um wissenschaftliches Wissen darzustellen, zu kuratieren und zu nutzen. Die systematische Wissensrepräsentation führt zu maschinenverarbeitbarem Wissen. Dieses ermöglicht es Maschinen wissenschaftliches Wissen mit minimalem menschlichen Eingriff zu verarbeiten. Um den Wissensgraphen zu generieren und zu kuratieren, schlagen wir einen Crowdsourcing-Ansatz vor, der durch maschinelles Lernen unterstützt wird, insbesondere durch natürliche Sprachverarbeitung (NLP). Derzeit sind NLP-Techniken nicht in der Lage, qualitativ hochwertiges wissenschaftliches Wissen auf autonome Weise zu extrahieren. Mit unserem vorgeschlagenen Ansatz verknüpfen wir menschliche und maschinelle Intelligenz und nutzen so die Stärken beider Ansätze. Zunächst erörtern wir strukturiertes wissenschaftliches Wissen, wobei wir den Open Research Knowledge Graph (ORKG) vorstellen.Insbesondere konzentrieren wir uns auf das Design und die Entwicklung der ORKG-Benutzeroberfläche (das Frontend). Eine der größten Herausforderungen besteht darin, eine Schnittstelle bereitzustellen, die leistungsfähig genug ist, um umfangreiche Wissensbeschreibungen zu erstellen und gleichzeitig intuitiv genug ist für Forscher ohne technischen Hintergrund, um solche Beschreibungen zu erstellen. Der ORKG dient als technische Grundlage für die Arbeit. Zweitens konzentrieren wir uns auf vergleichbares wissenschaftliches Wissen, wofür wir das Konzept der ORKG-Vergleiche einführen. ORKG-Vergleiche bieten maschinell verwertbare Übersichten über verwandtes wissenschaftliches Wissen in tabellarischer Form. Außerdem stellen wir eine Methode vor, mit der vorhandene Literaturübersichten genutzt werden können, um ORKG-Vergleiche mit Hilfe eines Human-in-the-Loop-Ansatzes zu erstellen. Darüber hinaus zeigen wir, wie ORKG-Vergleiche verwendet werden können, um ORKG SmartReviews zu erstellen. Die SmartReviews bieten dynamische Literaturübersichten in Form von lebenden Dokumenten. Sie stellen einen Versuch dar, die Hauptschwächen der gegenwärtigen Praxis des Literaturreviews zu beheben und zu skizzieren, wie die Zukunft der Veröffentlichung von Reviews aussehen kann. Drittens konzentrieren wir uns auf die Gestaltung geeigneter Aufgaben zur Generierung von wissenschaftlichem Wissen in einer Crowdsourced-Umgebung. Wir stellen eine intelligente Benutzeroberfläche vor, die es Forschern ermöglicht, Schlüsselsätze in wissenschaftlichen Publikationen mittles Diskursklassen zu annotieren. In diesem Prozess werden Forschende mit Vorschlägen von NLP-Tools unterstützt. Darüber hinaus stellen wir einen Ansatz zur Validierung von NLP-generierten Aussagen mit Hilfe von Mikroaufgaben in einer Crowdsourced-Umgebung vor. Mit diesem Ansatz senken wir die Hürde für die Eingabe von Daten in den ORKG und setzen Inhaltskonsumenten als Inhaltsersteller ein. Mit der Arbeit streben wir eine Transformation der wissenschaftlichen Kommunikation an, um die maschinelle Verwertbarkeit von wissenschaftlichem Wissen zu verbessern. Die Ansätze und Werkzeuge werden in einer Produktionsumgebung eingesetzt. Daher werden die meisten der vorgestellten Ansätze und Werkzeuge derzeit von verschiedenen Forschungsgemeinschaften aktiv genutzt und haben bereits einen Einfluss auf die wissenschaftliche Kommunikation.EC/ERC/819536/E

An Exploration of Representation Learning and Sequential Modeling Approaches for Supervised Topic Classification in Job Advertisements

This thesis applies the explorative double diamond design process borrowed to iteratively frame a research problem applicable in the context of a recruitment web service and then find the best approach to solve it. Thereby the problem focus is laid on multi-class classification, in particular the task of labelling sentences in job advertisements with one of six topics which were found to be covered in every typical job description. A dataset is obtained for evaluation and conventional N-Gram Vector Space models are compared with Representation Learning approaches, notably continuous distributed representations, and Sequential Modeling techniques using Recurrent Neural Networks. Results of the experiments show that the Representation Learning and Sequential Modeling approaches perform on par or better than traditional feature engineering methods and show a promising direction in and beyond research in Computational Linguistics and Natural Language Processing