Energyware engineering: techniques and tools for green software development

Tese de Doutoramento em Informática (MAP-i)Energy consumption is nowadays one of the most important concerns worldwide. While hardware is generally seen as the main culprit for a computer’s energy usage, software too has a tremendous impact on the energy spent, as it can cancel the efficiency introduced by the hardware. Green Computing is not a newfield of study, but the focus has been, until recently, on hardware. While there has been advancements in Green Software techniques, there is still not enough support for software developers so they can make their code more energy-aware, with various studies arguing there is both a lack of knowledge and lack of tools for energy-aware development. This thesis intends to tackle these two problems and aims at further pushing forward research on Green Software. This software energy consumption issue is faced as a software engineering question. By using systematic, disciplined, and quantifiable approaches to the development, operation, and maintenance of software we defined several techniques, methodologies, and tools within this document. These focus on providing software developers more knowledge and tools to help with energy-aware software development, or Energyware Engineering. Insights are provided on the energy influence of several stages performed during a software’s development process. We look at the energy efficiency of various popular programming languages, understanding which are the most appropriate if a developer’s concern is energy consumption. A detailed study on the energy profiles of different Java data structures is also presented, alongwith a technique and tool, further providing more knowledge on what energy efficient alternatives a developer has to choose from. To help developers with the lack of tools, we defined and implemented a technique to detect energy inefficient fragments within the source code of a software system. This technique and tool has been shown to help developers improve the energy efficiency of their programs, and even outperforming a runtime profiler. Finally, answers are provided to common questions and misconceptions within this field of research, such as the relationship between time and energy, and howone can improve their software’s energy consumption. This thesis provides a great effort to help support both research and education on this topic, helps continue to grow green software out of its infancy, and contributes to solving the lack of knowledge and tools which exist for Energyware Engineering.Hoje em dia o consumo energético é uma das maiores preocupações a nível global. Apesar do hardware ser, de umaforma geral, o principal culpado para o consumo de energia num computador, o software tem também um impacto significativo na energia consumida, pois pode anular, em parte, a eficiência introduzida pelo hardware. Embora Green Computing não seja uma área de investigação nova, o foco tem sido, até recentemente, na componente de hardware. Embora as técnicas de Green Software tenham vindo a evoluir, não há ainda suporte suficiente para que os programadores possam produzir código com consciencialização energética. De facto existemvários estudos que defendem que existe tanto uma falta de conhecimento como uma escassez de ferramentas para o desenvolvimento energeticamente consciente. Esta tese pretende abordar estes dois problemas e tem como foco promover avanços em green software. O tópico do consumo de energia é abordado duma perspectiva de engenharia de software. Através do uso de abordagens sistemáticas, disciplinadas e quantificáveis no processo de desenvolvimento, operação e manutencão de software, foi possível a definição de novas metodologias e ferramentas, apresentadas neste documento. Estas ferramentas e metodologias têm como foco dotar de conhecimento e ferramentas os programadores de software, de modo a suportar um desenvolvimento energeticamente consciente, ou Energyware Engineering. Deste trabalho resulta a compreensão sobre a influência energética a ser usada durante as diferentes fases do processo de desenvolvimento de software. Observamos as linguagens de programação mais populares sobre um ponto de vista de eficiência energética, percebendo quais as mais apropriadas caso o programador tenha uma preocupação com o consumo energético. Apresentamos também um estudo detalhado sobre perfis energéticos de diferentes estruturas de dados em Java, acompanhado por técnicas e ferramentas, fornecendo conhecimento relativo a quais as alternativas energeticamente eficientes que os programadores dispõem. Por forma a ajudar os programadores, definimos e implementamos uma técnica para detetar fragmentos energicamente ineficientes dentro do código fonte de um sistema de software. Esta técnica e ferramenta têm demonstrado ajudar programadores a melhorarem a eficiência energética dos seus programas e em algum casos superando um runtime profiler. Por fim, são dadas respostas a questões e conceções erradamente formuladas dentro desta área de investigação, tais como o relacionamento entre tempo e energia e como é possível melhorar o consumo de energia do software. Foi empregue nesta tese um esforço árduo de suporte tanto na investigação como na educação relativo a este tópico, ajudando à maturação e crescimento de green computing, contribuindo para a resolução da lacuna de conhecimento e ferramentas para suporte a Energyware Engineering.This work is partially funded by FCT – Foundation for Science and Technology, the Portuguese Ministry of Science, Technology and Higher Education, through national funds, and co-financed by the European Social Fund (ESF) through the Operacional Programme for Human Capital (POCH), with scholarship reference SFRH/BD/112733/2015. Additionally, funding was also provided the ERDF – European Regional Development Fund – through the Operational Programmes for Competitiveness and Internationalisation COMPETE and COMPETE 2020, and by the Portuguese Government through FCT project Green Software Lab (ref. POCI-01-0145-FEDER-016718), by the project GreenSSCM - Green Software for Space Missions Control, a project financed by the Innovation Agency, SA, Northern Regional Operational Programme, Financial Incentive Grant Agreement under the Incentive Research and Development System, Project No. 38973, and by the Luso-American Foundation in collaboration with the National Science Foundation with grant FLAD/NSF ref. 300/2015 and ref. 275/2016

Compiling Tree Transforms to Operate on Packed Representations

When written idiomatically in most programming languages, programs that traverse and construct trees operate over pointer-based data structures, using one heap object per-leaf and per-node. This representation is efficient for random access and shape-changing modifications, but for traversals, such as compiler passes, that process most or all of a tree in bulk, it can be inefficient. In this work we instead compile tree traversals to operate on pointer-free pre-order serializations of trees. On modern architectures such programs often run significantly faster than their pointer-based counterparts, and additionally are directly suited to storage and transmission without requiring marshaling. We present a prototype compiler, Gibbon, that compiles a small first-order, purely functional language sufficient for tree traversals. The compiler transforms this language into intermediate representation with explicit pointers into input and output buffers for packed data. The key compiler technologies include an effect system for capturing traversal behavior, combined with an algorithm to insert destination cursors. We evaluate our compiler on tree transformations over a real-world dataset of source-code syntax trees. For traversals touching the whole tree, such as maps and folds, packed data allows speedups of over 2x compared to a highly-optimized pointer-based baseline

The Role of Padel in Improving Physical Fitness and Health Promotion: Progress, Limitations, and Future Perspectives—A Narrative Review

Benefits of regular exercise for health are beyond any doubt. However, adherence to regular physical activity is an ongoing challenge. Among the options for exercise engagement, racket sports, and particularly padel, stand as emerging practices for children and adults to have fun, improve physical fitness, and potentially develop motor and cognitive skills. In the last decade, the literature on padel is increasing exponentially. However, there is a need for further experimental research. To design safe and effective sport-base physical activity promotion interventions, it is essential to have a deep understanding of the physical requirements, technical complexity, injury risks, and strength and conditioning programs. To assist researchers to conduct effective padel-based interventions for health, this review summarizes the state-of-the-art evidence about padel, identifies key topics to be addressed in the future, and discusses the potential role of padel as a physical fitness and health promotion strategy. A narrative review is presented, summarizing the results of padel articles from three different databases: Web of Science, Scopus, and Google Scholar. Studies written in Spanish and English were the inclusion criteria. The studies had to be published from 2000 onwards and be original, as well as peer-reviewed

Transient Typechecks are (Almost) Free

Transient gradual typing imposes run-time type tests that typically cause a linear slowdown in programs’ performance. This performance impact discourages the use of type annotations because adding types to a program makes the program slower. A virtual machine can employ standard justin-time optimizations to reduce the overhead of transient checks to near zero. These optimizations can give gradually-typed languages performance comparable to state-of-the-art dynamic languages, so programmers can add types to their code without affecting their programs’ performance

Optimizing Abstract Abstract Machines

The technique of abstracting abstract machines (AAM) provides a systematic approach for deriving computable approximations of evaluators that are easily proved sound. This article contributes a complementary step-by-step process for subsequently going from a naive analyzer derived under the AAM approach, to an efficient and correct implementation. The end result of the process is a two to three order-of-magnitude improvement over the systematically derived analyzer, making it competitive with hand-optimized implementations that compute fundamentally less precise results.Comment: Proceedings of the International Conference on Functional Programming 2013 (ICFP 2013). Boston, Massachusetts. September, 201