13 research outputs found

    Programming Languages and Systems

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    This open access book constitutes the proceedings of the 31st European Symposium on Programming, ESOP 2022, which was held during April 5-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 21 regular papers presented in this volume were carefully reviewed and selected from 64 submissions. They deal with fundamental issues in the specification, design, analysis, and implementation of programming languages and systems

    Design revolutions: IASDR 2019 Conference Proceedings. Volume 4: Learning, Technology, Thinking

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    In September 2019 Manchester School of Art at Manchester Metropolitan University was honoured to host the bi-annual conference of the International Association of Societies of Design Research (IASDR) under the unifying theme of DESIGN REVOLUTIONS. This was the first time the conference had been held in the UK. Through key research themes across nine conference tracks – Change, Learning, Living, Making, People, Technology, Thinking, Value and Voices – the conference opened up compelling, meaningful and radical dialogue of the role of design in addressing societal and organisational challenges. This Volume 4 includes papers from Learning, Technology and Thinking tracks of the conference

    How not to return to normal

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    In a March 2020 article published in Le Monde, Bruno Latour defined the Covid-19 emergency as "the big rehearsal" for the larger disaster to come: one that extends to all forms of life on Earth. The ongoing crisis, in his eyes, becomes both a risk and an opportunity to trial and develop new action plans necessary for the continuation of life. "The pandemic is a portal," wrote author Arundhati Roy a few days later, calling for a more equitable and sustainable post-pandemic future. The pandemic is an opportunity for un-learning and changing direction, particularly in how we approach risk and disaster. The dominant narrative for politicians and the media, however, is one of “returning to normal” as soon as possible, bouncing back, relying on established models of resilience based on the management of economic risk. They are also rehearsing, or modelling, worst- or best-case scenarios. Artists, designers, and institutions are shaping discourses around the growing extinguishment of our resources, but also performing, visualising, simulating and modelling responses to possible risks and imagining resilience differently. Design and art can foster new visions, pilot new modes of communication and knowledge sharing, and drive the interdisciplinary collaborations necessary to address common issues. This panel explores ways in which art and design practices can be mobilized to transform current approaches to risk and disaster in imaginative, sustainable and equitable ways. The papers selected for this session reflect a need to reassess, reframe, and reimagine the roles of museums, art and design, and thus contribute to a space for critical reflection to inform action, strategy, and practices. It is important to remember that our fields are far from immune from being complicit in the creation and reinforcement of the kinds of inequalities and injustices that have been made even more unmistakably clear in the last year: as Sasha Costanza-Shock, author of the book Design Justice, has pointed out, designers are ‘often unwittingly reproducing the existing structure of [...] who's going to benefit the most and who's going to be harmed the most by the tools or the objects or the systems or the buildings or spaces that we're designing.’ The urge to respond in an emergency, whether it's a design challenge in the context of COVID 19 or exhibition on climate change, requires space for critical thinking, inclusive conversation and production. This necessity comes across on the three papers brought together for this panel, and in the opening presentation by Emily Candela and Francesca Cavallo

    Políticas de Copyright de Publicações Científicas em Repositórios Institucionais: O Caso do INESC TEC

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    A progressiva transformação das práticas científicas, impulsionada pelo desenvolvimento das novas Tecnologias de Informação e Comunicação (TIC), têm possibilitado aumentar o acesso à informação, caminhando gradualmente para uma abertura do ciclo de pesquisa. Isto permitirá resolver a longo prazo uma adversidade que se tem colocado aos investigadores, que passa pela existência de barreiras que limitam as condições de acesso, sejam estas geográficas ou financeiras. Apesar da produção científica ser dominada, maioritariamente, por grandes editoras comerciais, estando sujeita às regras por estas impostas, o Movimento do Acesso Aberto cuja primeira declaração pública, a Declaração de Budapeste (BOAI), é de 2002, vem propor alterações significativas que beneficiam os autores e os leitores. Este Movimento vem a ganhar importância em Portugal desde 2003, com a constituição do primeiro repositório institucional a nível nacional. Os repositórios institucionais surgiram como uma ferramenta de divulgação da produção científica de uma instituição, com o intuito de permitir abrir aos resultados da investigação, quer antes da publicação e do próprio processo de arbitragem (preprint), quer depois (postprint), e, consequentemente, aumentar a visibilidade do trabalho desenvolvido por um investigador e a respetiva instituição. O estudo apresentado, que passou por uma análise das políticas de copyright das publicações científicas mais relevantes do INESC TEC, permitiu não só perceber que as editoras adotam cada vez mais políticas que possibilitam o auto-arquivo das publicações em repositórios institucionais, como também que existe todo um trabalho de sensibilização a percorrer, não só para os investigadores, como para a instituição e toda a sociedade. A produção de um conjunto de recomendações, que passam pela implementação de uma política institucional que incentive o auto-arquivo das publicações desenvolvidas no âmbito institucional no repositório, serve como mote para uma maior valorização da produção científica do INESC TEC.The progressive transformation of scientific practices, driven by the development of new Information and Communication Technologies (ICT), which made it possible to increase access to information, gradually moving towards an opening of the research cycle. This opening makes it possible to resolve, in the long term, the adversity that has been placed on researchers, which involves the existence of barriers that limit access conditions, whether geographical or financial. Although large commercial publishers predominantly dominate scientific production and subject it to the rules imposed by them, the Open Access movement whose first public declaration, the Budapest Declaration (BOAI), was in 2002, proposes significant changes that benefit the authors and the readers. This Movement has gained importance in Portugal since 2003, with the constitution of the first institutional repository at the national level. Institutional repositories have emerged as a tool for disseminating the scientific production of an institution to open the results of the research, both before publication and the preprint process and postprint, increase the visibility of work done by an investigator and his or her institution. The present study, which underwent an analysis of the copyright policies of INESC TEC most relevant scientific publications, allowed not only to realize that publishers are increasingly adopting policies that make it possible to self-archive publications in institutional repositories, all the work of raising awareness, not only for researchers but also for the institution and the whole society. The production of a set of recommendations, which go through the implementation of an institutional policy that encourages the self-archiving of the publications developed in the institutional scope in the repository, serves as a motto for a greater appreciation of the scientific production of INESC TEC

    Paralelização do algoritmo de indexação de dados multimídia baseado em quantização

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    Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2019.A busca por similaridade em espaços de alta dimensionalidade é uma operação fundamental em diversas aplicações de recuperação de dados multimídia, no entanto essa operação é tipicamente uma das mais computacionalmente caras. Alguns métodos propõem a busca aproximada para minimizar esse problema, uma alternativa que tenta fazer um compromisso entre o custo computacional e a precisão da busca. Um dos métodos baseados em busca aproximada é o Product Quantization for Approximate Nearest Neighbor Search (PQANNS), que propõe a decomposição do espaço de busca em um produto cartesiano de subespaços de baixa dimensionalidade e a quantização de cada um deles separadamente. Para tanto, é utilizada uma estrutura de lista invertida para fazer a indexação dos dados, o que permite a realização de buscas não-exaustivas. A redução da dimensionalidade dos dados aliada à busca não-exaustiva faz com que o PQANNS responda consultas de forma eficiente e com baixa demanda de memória, no entanto sua execução sequencial ainda é limitada a trabalhar com bases que caibam na memória RAM de apenas uma máquina. Nosso objetivo é propor uma paralelização em memória distribuída do PQANNS, sendo assim capaz de lidar com grandes bases de dados. Também propomos uma paralelização em máquina multicore, visando reduzir o tempo de resposta às consultas e utilizar toda a capacidade de processamento disponível. Nossa paralelização em memória distribuída foi avaliada utilizando 128 nós/3584 núcleos de CPU, obtendo uma eficiência de 0.97 e foi capaz de realizar a indexação e busca em uma base de dados contendo 256 bilhões de vetores Scale Invariant Feature Transform (SIFT). Além disso, a execução da nossa paralelização em máquina multicore obteve um excelente ganho em desempenho com até 28 núcleos, obtendo um speedup médio de 26, 36x utilizando todos os núcleos.The search for similarity in high dimensional spaces is a core operation found in several multimedia retrieval applications. However this operation is typically one of the most computationally expensive. Some methods propose an approximate search to minimize this problem, trying to make a trade-off between computational cost and search precision. One of these methods is the Product Quantization for Approximate Nearest Neighbor Search (PQANNS), which proposes the decomposition of the search space into a Cartesian product of low-dimensional subspaces and the quantization of each of them separately. In order to do so, an inverted file structure is used to index the data, which allows non-exhaustive searches. The reduction of data dimensionality coupled with the non-exhaustive search causes the PQANNS to respond efficiently and with low memory requirements, however its sequential execution is still limited to working with bases that fit into the RAM memory of a single machine. Our goal is to propose a parallelization strategy that works on distributed memory plataforms of PQANNS, thus being able to handle large databases. We also propose a multicore machine parallelization, in order to reduce the response time to the queries and to use all available processing capacity. Our distributed memory parallelization was evaluated using 128 nodes/3584 CPU cores, obtaining an efficiency of 0.97 and was able to perform the index and search in a database containing 256 billion Scale Invariant Feature Transform (SIFT) vectors. In addition, the execution of our parallelization in a multicore machine obtained a performance gain with up to 28 cores, obtaining an average speedup of 26.36x using all the cores

    Aldo von Wangenheim

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    Design and Evaluation of Low-Latency Communication Middleware on High Performance Computing Systems

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    [Resumen]El interés en Java para computación paralela está motivado por sus interesantes características, tales como su soporte multithread, portabilidad, facilidad de aprendizaje,alta productividad y el aumento significativo en su rendimiento omputacional. No obstante, las aplicaciones paralelas en Java carecen generalmente de mecanismos de comunicación eficientes, los cuales utilizan a menudo protocolos basados en sockets incapaces de obtener el máximo provecho de las redes de baja latencia, obstaculizando la adopción de Java en computación de altas prestaciones (High Per- formance Computing, HPC). Esta Tesis Doctoral presenta el diseño, implementación y evaluación de soluciones de comunicación en Java que superan esta limitación. En consecuencia, se desarrollaron múltiples dispositivos de comunicación a bajo nivel para paso de mensajes en Java (Message-Passing in Java, MPJ) que aprovechan al máximo el hardware de red subyacente mediante operaciones de acceso directo a memoria remota que proporcionan comunicaciones de baja latencia. También se incluye una biblioteca de paso de mensajes en Java totalmente funcional, FastMPJ, en la cual se integraron los dispositivos de comunicación. La evaluación experimental ha mostrado que las primitivas de comunicación de FastMPJ son competitivas en comparación con bibliotecas nativas, aumentando significativamente la escalabilidad de aplicaciones MPJ. Por otro lado, esta Tesis analiza el potencial de la computación en la nube (cloud computing) para HPC, donde el modelo de distribución de infraestructura como servicio (Infrastructure as a Service, IaaS) emerge como una alternativa viable a los sistemas HPC tradicionales. La evaluación del rendimiento de recursos cloud específicos para HPC del proveedor líder, Amazon EC2, ha puesto de manifiesto el impacto significativo que la virtualización impone en la red, impidiendo mover las aplicaciones intensivas en comunicaciones a la nube. La clave reside en un soporte de virtualización apropiado, como el acceso directo al hardware de red, junto con las directrices para la optimización del rendimiento sugeridas en esta Tesis.[Resumo]O interese en Java para computación paralela está motivado polas súas interesantes características, tales como o seu apoio multithread, portabilidade, facilidade de aprendizaxe, alta produtividade e o aumento signi cativo no seu rendemento computacional. No entanto, as aplicacións paralelas en Java carecen xeralmente de mecanismos de comunicación e cientes, os cales adoitan usar protocolos baseados en sockets que son incapaces de obter o máximo proveito das redes de baixa latencia, obstaculizando a adopción de Java na computación de altas prestacións (High Performance Computing, HPC). Esta Tese de Doutoramento presenta o deseño, implementaci ón e avaliación de solucións de comunicación en Java que superan esta limitación. En consecuencia, desenvolvéronse múltiples dispositivos de comunicación a baixo nivel para paso de mensaxes en Java (Message-Passing in Java, MPJ) que aproveitan ao máaximo o hardware de rede subxacente mediante operacións de acceso directo a memoria remota que proporcionan comunicacións de baixa latencia. Tamén se inclúe unha biblioteca de paso de mensaxes en Java totalmente funcional, FastMPJ, na cal foron integrados os dispositivos de comunicación. A avaliación experimental amosou que as primitivas de comunicación de FastMPJ son competitivas en comparación con bibliotecas nativas, aumentando signi cativamente a escalabilidade de aplicacións MPJ. Por outra banda, esta Tese analiza o potencial da computación na nube (cloud computing) para HPC, onde o modelo de distribución de infraestrutura como servizo (Infrastructure as a Service, IaaS) xorde como unha alternativa viable aos sistemas HPC tradicionais. A ampla avaliación do rendemento de recursos cloud específi cos para HPC do proveedor líder, Amazon EC2, puxo de manifesto o impacto signi ficativo que a virtualización impón na rede, impedindo mover as aplicacións intensivas en comunicacións á nube. A clave atópase no soporte de virtualización apropiado, como o acceso directo ao hardware de rede, xunto coas directrices para a optimización do rendemento suxeridas nesta Tese.[Abstract]The use of Java for parallel computing is becoming more promising owing to its appealing features, particularly its multithreading support, portability, easy-tolearn properties, high programming productivity and the noticeable improvement in its computational performance. However, parallel Java applications generally su er from inefficient communication middleware, most of which use socket-based protocols that are unable to take full advantage of high-speed networks, hindering the adoption of Java in the High Performance Computing (HPC) area. This PhD Thesis presents the design, development and evaluation of scalable Java communication solutions that overcome these constraints. Hence, we have implemented several lowlevel message-passing devices that fully exploit the underlying network hardware while taking advantage of Remote Direct Memory Access (RDMA) operations to provide low-latency communications. Moreover, we have developed a productionquality Java message-passing middleware, FastMPJ, in which the devices have been integrated seamlessly, thus allowing the productive development of Message-Passing in Java (MPJ) applications. The performance evaluation has shown that FastMPJ communication primitives are competitive with native message-passing libraries, improving signi cantly the scalability of MPJ applications. Furthermore, this Thesis has analyzed the potential of cloud computing towards spreading the outreach of HPC, where Infrastructure as a Service (IaaS) o erings have emerged as a feasible alternative to traditional HPC systems. Several cloud resources from the leading IaaS provider, Amazon EC2, which speci cally target HPC workloads, have been thoroughly assessed. The experimental results have shown the signi cant impact that virtualized environments still have on network performance, which hampers porting communication-intensive codes to the cloud. The key is the availability of the proper virtualization support, such as the direct access to the network hardware, along with the guidelines for performance optimization suggested in this Thesis

    Techniques of High Performance Reservoir Simulation for Unconventional Challenges

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    The quest to improve the performance of reservoir simulators has been evolving with the newly encountered challenges of modeling more complex recovery mechanisms and related phenomena. Reservoir subsidence, fracturing and fault reactivation etc. require coupled flow and poroelastic simulation. These features, in turn, bring a heavy burden on linear solvers. The booming unconventional plays such as shale/tight oil in North America demand reservoir simulation techniques to handle more physics (or more hypotheses). This dissertation deals with three aspects in improving the performance of reservoir simulation toward these unconventional challenges. Compositional simulation is often required for many reservoir studies with complex recovery mechanisms such as gas inject. But, it is time consuming and its parallelization often suffers sever load imbalance problems. In the first section, a novel approach based on domain over-decomposition is investigated and implemented to improve the parallel performance of compositional simulation. For a realistic reservoir case, it is shown the speedup is improved from 29.27 to 62.38 on 64 processors using this technique. Another critical part that determines the performance of a reservoir simulator is the linear solver. In the second section, a new type of linear solver based the combinatorial multilevel method (CML) is introduced and investigated for several reservoir simulation applications. The results show CML has better scalability and performance empirically and is well-suited for coupled poroelastic problems. These results also suggest that CML might be a promising way of precondition for flow simulation with and without coupled poroelastic calculations. In order to handle unconventional petroleum fluid properties for tight oil, the third section incorporates a simulator with extended vapor-liquid equilibrium calculations to consider the capillarity effect caused by the dynamic nanopore properties. The enhanced simulator can correctly capture the pressure dependent impact of the nanopore on rock and fluid properties. It is shown inclusion of these enhanced physics in simulation will lead to significant improvements in field operation decision-making and greatly enhance the reliability of recovery predictions

    A (ir)regularity-aware task scheduler for heterogeneous platforms

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    This paper addresses the design, implementation and validation of an e ective scheduling scheme for both regular and irregular applications on heterogeneous platforms. The scheduler uses an empirical performance model to dynamically schedule the workload, organized into a given number of chunks, and follows the Heterogeneous Earliest Finish Time (HEFT) scheduling algorithm, which ranks the tasks based on both their computation and communication costs. The evaluation of the proposed approach is based on three case studies { the SAXPY, the FFT and the Barnes-Hut algorithms { two regular and one irregular application. The scheduler was evaluated on a heterogeneous platform with one quad-core CPU-chip accelerated by one or two GPU devices, embedded in the GAMA framework. The evaluation runs measured the e ectiveness, the e ciency and the scalability of the proposed method. Results show that the proposed model was e active in addressing both regular and irregular applications, on heterogeneous platforms, while achieving ideal ( 100%) levels of e ciency in the irregular Barnes-Hut algorithm.Fundação para a Ciência e Tecnologi
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