Heterogeneous computing with an algorithmic skeleton framework

The Graphics Processing Unit (GPU) is present in almost every modern day personal computer. Despite its specific purpose design, they have been increasingly used for general computations with very good results. Hence, there is a growing effort from the community to seamlessly integrate this kind of devices in everyday computing. However, to fully exploit the potential of a system comprising GPUs and CPUs, these devices should be presented to the programmer as a single platform. The efficient combination of the power of CPU and GPU devices is highly dependent on each device’s characteristics, resulting in platform specific applications that cannot be ported to different systems. Also, the most efficient work balance among devices is highly dependable on the computations to be performed and respective data sizes. In this work, we propose a solution for heterogeneous environments based on the abstraction level provided by algorithmic skeletons. Our goal is to take full advantage of the power of all CPU and GPU devices present in a system, without the need for different kernel implementations nor explicit work-distribution.To that end, we extended Marrow, an algorithmic skeleton framework for multi-GPUs, to support CPU computations and efficiently balance the work-load between devices. Our approach is based on an offline training execution that identifies the ideal work balance and platform configurations for a given application and input data size. The evaluation of this work shows that the combination of CPU and GPU devices can significantly boost the performance of our benchmarks in the tested environments, when compared to GPU-only executions.

A framework for efficient model transformations

The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.

Towards an algorithmic skeleton framework for programming the Intel R Xeon PhiTM processor

The Intel R Xeon PhiTM is the first processor based on Intel’s MIC (Many Integrated Cores) architecture. It is a co-processor specially tailored for data-parallel computations, whose basic architectural design is similar to the ones of GPUs (Graphics Processing Units), leveraging the use of many integrated low computational cores to perform parallel computations. The main novelty of the MIC architecture, relatively to GPUs, is its compatibility with the Intel x86 architecture. This enables the use of many of the tools commonly available for the parallel programming of x86-based architectures, which may lead to a smaller learning curve. However, programming the Xeon Phi still entails aspects intrinsic to accelerator-based computing, in general, and to the MIC architecture, in particular. In this thesis we advocate the use of algorithmic skeletons for programming the Xeon Phi. Algorithmic skeletons abstract the complexity inherent to parallel programming, hiding details such as resource management, parallel decomposition, inter-execution flow communication, thus removing these concerns from the programmer’s mind. In this context, the goal of the thesis is to lay the foundations for the development of a simple but powerful and efficient skeleton framework for the programming of the Xeon Phi processor. For this purpose we build upon Marrow, an existing framework for the orchestration of OpenCLTM computations in multi-GPU and CPU environments. We extend Marrow to execute both OpenCL and C++ parallel computations on the Xeon Phi. We evaluate the newly developed framework, several well-known benchmarks, like Saxpy and N-Body, will be used to compare, not only its performance to the existing framework when executing on the co-processor, but also to assess the performance on the Xeon Phi versus a multi-GPU environment.

Framework for the semantic alignment of enterprise’s domain knowledge

Nowadays, the consumption of goods and services on the Internet are increasing in a constant motion. Small and Medium Enterprises (SMEs) mostly from the traditional industry sectors are usually make business in weak and fragile market sectors, where customized products and services prevail. To survive and compete in the actual markets they have to readjust their business strategies by creating new manufacturing processes and establishing new business networks through new technological approaches. In order to compete with big enterprises, these partnerships aim the sharing of resources, knowledge and strategies to boost the sector’s business consolidation through the creation of dynamic manufacturing networks. To facilitate such demand, it is proposed the development of a centralized information system, which allows enterprises to select and create dynamic manufacturing networks that would have the capability to monitor all the manufacturing process, including the assembly, packaging and distribution phases. Even the networking partners that come from the same area have multi and heterogeneous representations of the same knowledge, denoting their own view of the domain. Thus, different conceptual, semantic, and consequently, diverse lexically knowledge representations may occur in the network, causing non-transparent sharing of information and interoperability inconsistencies. The creation of a framework supported by a tool that in a flexible way would enable the identification, classification and resolution of such semantic heterogeneities is required. This tool will support the network in the semantic mapping establishments, to facilitate the various enterprises information systems integration.

Methodological framework for detection of harmonisation breaking in service environments

As the complexity of markets and the dynamicity of systems evolve, the need for interoperable systems capable of strengthening enterprise communication effectiveness increases. This is particularly significant when it comes to collaborative enterprise networks, like manufacturing supply chains, where several companies work, communicate, and depend on each other, in order to achieve a specific goal. Once interoperability is achieved, that is once all network parties are able to communicate with and understand each other, organisations are able to exchange information along a stable environment that follows agreed laws. However, as markets adapt to new requirements and demands, an evolutionary behaviour is triggered giving space to interoperability problems, thus disrupting the sustainability of interoperability and raising the need to develop monitoring activities capable of detecting and preventing unexpected behaviour. This work seeks to contribute to the development of monitoring techniques for interoperable SOA-based enterprise networks. It focuses on the automatic detection of harmonisation breaking events during real-time communications, and strives to develop and propose a methodological approach to handle these disruptions with minimal or no human intervention, hence providing existing service-based networks with the ability to detect and promptly react to interoperability issues.

A segurança das infraestruturas críticas em Portugal

Portugal, having responsibilities at European level, needs to ensure compliance with European standards, particularly with regard to the European Security Plan for Critical Infrastructures. National critical infrastructures should be a focus of attention with regard to the management of public risks, since these represent "a set of services that are essential to the functioning of the country and the functioning of the forces that ensure national defense." (Soares, 2008) This contribution on national critical infrastructures (CI) has the essential objective of clarifying the development of the strategy adopted by Portugal in pursuit of the security of these fundamental infrastructures. The goal lies not only through producing a descriptive document, but also carry a brief confrontation between the legal framework related to these subjects and the reality in which the Critical Infrastructure Operators and the National Civil Protection Authority (ANPC) operate. It is intended, in this sense, to understand the development of the project for the national security program of critical infrastructures and what effects of its measures on operators. As for the methodology, we followed a methodological strategy, where we combine the literature with data obtained through semi-structured interviews. Portugal, being a geographically peripheral country and having no record of incidents capable of causing major contingencies in key services for the normal development of society, does not have a structured and regulator plan that substantiates the need for operators responsible for CI to invest in security. This same approach is expected at the State level, believing that even though this theme has be widely explored by international institutions, Portugal has not yet tried to give the attention it deserves. Without the existence of an institution and a regulatory system, CI operators can become less available to comply with the legal framework.

DYNAMOD – A dynamic agent based modelling framework for digital businesses

Digital Businesses have become a major driver for economic growth and have seen an explosion of new startups. At the same time, it also includes mature enterprises that have become global giants in a relatively short period of time. Digital Businesses have unique characteristics that make the running and management of a Digital Business much different from traditional offline businesses. Digital businesses respond to online users who are highly interconnected and networked. This enables a rapid flow of word of mouth, at a pace far greater than ever envisioned when dealing with traditional products and services. The relatively low cost of incremental user addition has led to a variety of innovation in pricing of digital products, including various forms of free and freemium pricing models. This thesis explores the unique characteristics and complexities of Digital Businesses and its implications on the design of Digital Business Models and Revenue Models. The thesis proposes an Agent Based Modeling Framework that can be used to develop Simulation Models that simulate the complex dynamics of Digital Businesses and the user interactions between users of a digital product. Such Simulation models can be used for a variety of purposes such as simple forecasting, analysing the impact of market disturbances, analysing the impact of changes in pricing models and optimising the pricing for maximum revenue generation or a balance between growth in usage and revenue generation. These models can be developed for a mature enterprise with a large historical record of user growth rate as well as for early stage enterprises without much historical data. Through three case studies, the thesis demonstrates the applicability of the Framework and its potential applications.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

The Beglocal framework applied to B2C E-commerce

This case-study examined the use of the BeGloCal Framework applied to B2C E-commerce, for a fast moving consumer goods European manufacturing firm. It explains how the framework supported the team within the company to identify the right local market as to where to start the project, the problem for the company was to find the most appealing area to invest resources. By going through all the steps of the framework the findings led the company to London (Kensington and Chelsea). It shows how managers should act when they have to find a trade-off between standardization and adaptation.

A new credit monitoring framework for agents' networks

The purpose of this work is to develop a practicable approach for Telecom firms to manage the credit risk exposition to their commercial agents’ network. Particularly it will try to approach the problem of credit concession to clients’ from a corporation perspective and explore the particular scenario of agents that are part of the commercial chain of the corporation and therefore are not end-users. The agents’ network that served as a model for the presented study is composed by companies that, at the same time, are both clients and suppliers of the Telecommunication Company. In that sense the credit exposition analysis must took into consideration all financial fluxes, both inbound and outbound. The current strain on the Financial Sector in Portugal, and other peripheral European economies, combined with the high leverage situation of most companies, generates an environment prone to credit default risk. Due to these circumstances managing credit risk exposure is becoming increasingly a critical function for every company Financial Department. The approach designed in the current study combined two traditional risk monitoring tools: credit risk scoring and credit limitation policies. The objective was to design a new credit monitoring framework that is more flexible, uses both external and internal relationship history to assess risk and takes into consideration commercial objectives inside the agents’ network. Although not explored at length, the blueprint of a Credit Governance model was created for implementing the new credit monitoring framework inside the telecom firm. The Telecom Company that served as a model for the present work decided to implement the new Credit Monitoring framework after this was presented to its Executive Commission.

Crowdfunding

Crowdfunding, as we know it today, is a very recent activity that was born almost accidentally in the end of the 90’s decade. Due to the advent of the internet and the social networks, entrepreneurs are now able to promote their projects to a very large community. Whether it is composed by family, friends, acquaintances or simply people that are interested in the same topic or share the passion, the community is able to fund new ventures by individually investing modest amounts of money. In return, the entrepreneur can offer symbolic rewards, shares or other financial returns. New crowdfunding platforms are born almost every day all over the world, offering a new way of raising capital for their projects or a new way to invest their money in innovative ventures. Although crowdfunding is still finding its place in the financial services, successful cases such as Kickstarter demonstrate the power of the crowd in boosting creativity and productivity, financing thousands of projects by raising millions of dollars from thousands of investors. Due to regulatory restrictions, the most prominent model for now is reward-based crowdfunding, where the investors are prized with symbolic returns or privileged access to the products or services offered by the entrepreneurs. Other models such as peer-to-peer lending are also surging, allowing borrowers access to capital at a lower cost compared to so-called traditional financial institutions, and offering lenders a higher rate of return. But when it comes to offering shares to investors, i.e. using equity-based crowdfunding, entrepreneurs face regulatory obstacles in almost every country, where legislation was passed decades ago with the objective of promoting financially-capable ventures and protecting investors. Access to capital has become more difficult after the global economic recession of 2008, and for most countries it will not get easier in the near future, leaving start-ups and small enterprises with few options to start or expand their operations. In this study we attempt to answer the following research questions: how has equity-based crowdfunding evolved since its creation? Where and how has equity-based crowdfunding been implemented so far? What are the constraints and opportunities for implementing equity-crowdfunding in the world, and more particularly in Portugal? Finally, we will discuss the risks of crowdfunding and reflect on the future of this industry.

Understanding impact readiness in Portugal’s social sector and designing a framework for capacity-building for social impact

This project is based on the theme of capacity-building in social organisations to improve their impact readiness, which is the predictability of delivering intended outcomes. All organisations which have a social mission, non-profit or for-profit, will be considered to fall within the social sector for the purpose of this work. The thesis will look at (i) what is impact readiness and what are the considerations for building impact readiness in social organisations, (ii) what is the international benchmark in measuring and building impact readiness, (iii) understand the impact readiness of Portuguese social organisations and the supply of capacity building for social impact in Portugal currently, and (iv) provide recommendations on the design of a framework for capacity building for impact readiness adapted to the Portuguese context. This work is of particular relevance to the Social Investment Laboratory, which is a sponsor of this project, in its policy work as part of the Portuguese Social Investment Taskforce (the “Taskforce”). This in turn will inform its contribution to the set-up of Portugal Inovação Social, a wholesaler catalyst entity of social innovation and social investment in the country, launched in early 2015. Whilst the output of this work will be set a recommendations for wider application for capacity-building programmes in Portugal, Portugal Inovação Social will also clearly have a role in coordinating the efforts of market players – foundations, corporations, public sector and social organisations – in implementing these recommendations. In addition, the findings of this report could have relevance to other countries seeking to design capacity building frameworks in their local markets and to any impact-driven organisations with an interest in enhancing the delivery of impact within their work.

Does the existing Corporate Governance structure and strict Legal Framework, affect the strategic decisionmaking of CEOs?

This thesis is a case study on Corporate Governance and Business Ethics, using the Portuguese Corporate Law as a general setting. The thesis was conducted in Portugal with illustrations on past cases under the Business Judgment Rule of the State of Delaware, U.SA along with illustrations on current cases in Portugal under the Portuguese Judicial setting, along with a comparative analysis between both. A debate is being considered among scholars and executives; a debate on best practices within corporate governance and corporate law, associated with recent discoveries of unlawful investments that lead to the bankruptcy of leading institutions and an aggravation of the crisis in Portugal. The study aimed at learning possible reasons and causes for the current situation of the country’s corporations along with attempts to discover the best way to move forward. From the interviews and analysis conducted, this paper concluded that the corporate governance structure and legal frameworks in Portugal were not the sole influencers behind the actions and decisions of Corporate Executives, nor were they the main triggers for the recent corporate mishaps. But it is rather a combination of different factors that played a significant role, such as cultural and ethical aspects, individual personalities, and others all of which created gray areas beyond the legal structure, which in turn accelerated and aggravated the corporate governance crisis in the country.