Programming Abstractions for Data Locality

The goal of the workshop and this report is to identify common themes and standardize concepts for locality-preserving abstractions for exascale programming models. Current software tools are built on the premise that computing is the most expensive component, we are rapidly moving to an era that computing is cheap and massively parallel while data movement dominates energy and performance costs. In order to respond to exascale systems (the next generation of high performance computing systems), the scientific computing community needs to refactor their applications to align with the emerging data-centric paradigm. Our applications must be evolved to express information about data locality. Unfortunately current programming environments offer few ways to do so. They ignore the incurred cost of communication and simply rely on the hardware cache coherency to virtualize data movement. With the increasing importance of task-level parallelism on future systems, task models have to support constructs that express data locality and affinity. At the system level, communication libraries implicitly assume all the processing elements are equidistant to each other. In order to take advantage of emerging technologies, application developers need a set of programming abstractions to describe data locality for the new computing ecosystem. The new programming paradigm should be more data centric and allow to describe how to decompose and how to layout data in the memory.Fortunately, there are many emerging concepts such as constructs for tiling, data layout, array views, task and thread affinity, and topology aware communication libraries for managing data locality. There is an opportunity to identify commonalities in strategy to enable us to combine the best of these concepts to develop a comprehensive approach to expressing and managing data locality on exascale programming systems. These programming model abstractions can expose crucial information about data locality to the compiler and runtime system to enable performance-portable code. The research question is to identify the right level of abstraction, which includes techniques that range from template libraries all the way to completely new languages to achieve this goal

Adaptation based on learning style and knowledge level in e-learning systems

Although there have been numerous attempts to build and evaluate adaptive e-learning systems, they tend to be limited in scope, and suffer from a lack of carefully designed and controlled experimental evaluations of their effectiveness and usability. This thesis addresses these issues through the implementation of an adaptive e-learning system and its experimental validation. The design of an adaptive framework and the specific instantiation of its components into a configurable adaptive e-learning system are presented. The domain model of the system deals with computer security. The learner model incorporates the information perception dimension of the Felder-Silverman model of learning style and also knowledge level. The adaptation model generates personalised learning paths and offers adaptive guidance and recommendation. The thesis also provides an empirical evaluation through three controlled experiments to investigate the effect of different forms of adaptation. Rigorous experimental design, careful investigation and precise reporting of results are taken into account in all the three experiments. The findings indicate that matching the sequence of learning objects to the information perception learning style yields significantly better learning outcome and learner satisfaction than non-matching sequences. They also indicate that adaptation based on the combination of the information perception learning style and knowledge level yields significantly better learning outcome (both in the short- and long-term) and learner satisfaction than adaptation based on either of these learner characteristics alone; this combination is also marked by a significantly higher level of perceived usability compared to a non-adaptive version of the e-learning system

Simplifying Authoring of Adaptive Hypermedia Structures in an eLearning Context

Full version unavailable due to 3rd party copyright restrictions.In an eLearning context, Adaptive Hypermedia Systems have been developed to improve learning success by increasing learner satisfaction, learning speed, and educational effectiveness. However, creating adaptive eLearning content and structures is still a time consuming and complicated task, in particular if individual lecturers are the intended authors. The way of thinking that is needed to create adaptive structures as well as the workflows is one that lecturers are unaccustomed to. The aim of this research project is to develop a concept that helps authors create adaptive eLearning content and structures, which focuses on its applicability for lecturers as intended authors. The research is targeted at the sequencing of content, which is one of the main aspects of adaptive eLearning. To achieve this aim the problem has been viewed from the author’s side. First, in terms of complexity of thoughts and threads, explanations about content structures have been found in storytelling theory. It also provides insights into how authors work, how story worlds are created, story lines intertwined, and how they are all merged together into one content. This helps us understand how non technical authors create content that is understandable and interesting for recipients. Second, the linear structure of learning content has been investigated to extract all the information that can be used for sequencing purposes. This investigation led to an approach that combines existing models to ease the authoring process for adaptive learning content by relating linear content from different authors and therefore defining interdependencies that delinearise the content structure. The technical feasibility of the authoring methods for adaptive learning content has been proven by the implementation of the essential parts in a research prototype and by authoring content from real life lectures with the prototype’s editor. The content and its adaptive structure obtained by using the concept of this research have been tested with the prototype’s player and monitor. Additionally, authoring aspects of the concept have been shown along with practical examples and workflows. Lastly, the interviewees who took part in expert interviews have agreed that the concept significantly reduces authoring complexity and potentially increases the amount of lecturers that are able to create adaptive content. The concept represents the common and traditional authoring process for linear content to a large extent. Compared to existing approaches the additional work needed is limited, and authors do not need to delve into adaptive structures or other authors’ content structures and didactic approaches

Semantic Selection of Internet Sources through SWRL Enabled OWL Ontologies

This research examines the problem of Information Overload (IO) and give an overview of various attempts to resolve it. Furthermore, argue that instead of fighting IO, it is advisable to start learning how to live with it. It is unlikely that in modern information age, where users are producer and consumer of information, the amount of data and information generated would decrease. Furthermore, when managing IO, users are confined to the algorithms and policies of commercial Search Engines and Recommender Systems (RSs), which create results that also add to IO. this research calls to initiate a change in thinking: this by giving greater power to users when addressing the relevance and accuracy of internet searches, which helps in IO. However powerful search engines are, they do not process enough semantics in the moment when search queries are formulated. This research proposes a semantic selection of internet sources, through SWRL enabled OWL ontologies. the research focuses on SWT and its Stack because they (a)secure the semantic interpretation of the environments where internet searches take place and (b) guarantee reasoning that results in the selection of suitable internet sources in a particular moment of internet searches. Therefore, it is important to model the behaviour of users through OWL concepts and reason upon them in order to address IO when searching the internet. Thus, user behaviour is itemized through user preferences, perceptions and expectations from internet searches. The proposed approach in this research is a Software Engineering (SE) solution which provides computations based on the semantics of the environment stored in the ontological model

Ontology-based personalisation of e-learning resources for disabled students

Students with disabilities are often expected to use e-learning systems to access learning materials but most systems do not provide appropriate adaptation or personalisation to meet their needs.The difficulties related to inadaptability of current learning environments can now be resolved using semantic web technologies such as web ontologies which have been successfully used to drive e-learning personalisation. Nevertheless, e-learning personalisation for students with disabilities has mainly targeted those with single disabilities such as dyslexia or visual impairment, often neglecting those with multiple disabilities due to the difficulty of designing for a combination of disabilities.This thesis argues that it is possible to personalise learning materials for learners with disabilities, including those with multiple disabilities. This is achieved by developing a model that allows the learning environment to present the student with learning materials in suitable formats while considering their disability and learning needs through an ontology-driven and disability-aware personalised e-learning system model (ONTODAPS). A disability ontology known as the Abilities and Disabilities Ontology for Online LEarning and Services (ADOOLES) is developed and used to drive this model. To test the above hypothesis, some case studies are employed to show how the model functions for various individuals with and without disabilities and then the implemented visual interface is experimentally evaluated by eighteen students with disabilities and heuristically by ten lecturers. The results are collected and statistically analysed.The results obtained confirm the above hypothesis and suggest that ONTODAPS can be effectively employed to personalise learning and to manage learning resources. The student participants found that ONTODAPS could aid their learning experience and all agreed that they would like to use this functionality in an existing learning environment. The results also suggest that ONTODAPS provides a platform where students with disabilities can have equivalent learning experience with their peers without disabilities. For the results to be generalised, this study could be extended through further experiments with more diverse groups of students with disabilities and across multiple educational institutions

Designing wearable technologies for spatial awareness and social interactions

Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 93-96).We live in an era of constant connectedness; we carry a smartphone in our pocket, headsets on our ears and enjoy limitless and regular access to almost any content we wish. However, the use of the personal computing devices that allow this connection with the virtual world damages our ability to connect with the physical world surrounding us; our eyes are focused on screens, our ears are covered by headphones and our attention jumps between apps. As a result, many of us are actually finding it harder to have face to face interactions with others than ever before. We are getting worse at communicating with the people around us, in the present, and tend to prefer virtual alternatives, as they are easier to operate, less stressful and fully under our control. This thesis proposes a perspective at wearable and personal computing devices and the role that their design may play in creating and fighting the epidemic of growing isolation. We hypothesize that the negative social trends that we witness as a result of using smartphones, headphones and other personal devices are not the purpose of these technologies, but rather an unwanted byproduct of their use. We propose to redesign ubiquitous personal technologies to reduce their isolating effect and use them to foster more physical interpersonal interactions and spatial awareness, by equipping them with additional modes of operation that force interpersonal interaction. We call this family of new interfaces IceBreakware. As a proof of concept, we present LeakyPhones, an instance of IceBreakware and a social version of the ubiquitous headphones. LeakyPhones is an interface that allows colocated and real time audio sharing between two or more people by coupling music sharing with a gaze. LeakyPhones encourages users to explore their surroundings with their eyes, and interact with the people around them. They also change the meaning of a previously private medium such as the headphones and turn it into public at will. By doing this, Leakyphones tries to overcome some of the limitations of normal headphones. This work explores corrective measures to standard personal devices that can possibly be implemented to existing technologies in order to encourage desired social behaviors. It demonstrates how gaze and music sharing may act as a social vehicle and help and encourage positive real-world interactions between people while not substituting them with virtual alternatives.by Amos Golan.S.M

Knowledge and Management Models for Sustainable Growth

In the last years sustainability has become a topic of global concern and a key issue in the strategic agenda of both business organizations and public authorities and organisations. Significant changes in business landscape, the emergence of new technology, including social media, the pressure of new social concerns, have called into question established conceptualizations of competitiveness, wealth creation and growth. New and unaddressed set of issues regarding how private and public organisations manage and invest their resources to create sustainable value have brought to light. In particular the increasing focus on environmental and social themes has suggested new dimensions to be taken into account in the value creation dynamics, both at organisations and communities level. For companies the need of integrating corporate social and environmental responsibility issues into strategy and daily business operations, pose profound challenges, which, in turn, involve numerous processes and complex decisions influenced by many stakeholders. Facing these challenges calls for the creation, use and exploitation of new knowledge as well as the development of proper management models, approaches and tools aimed to contribute to the development and realization of environmentally and socially sustainable business strategies and practices

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp