13 resultados para Performance improvements
em Universidad Politécnica de Madrid
Resumo:
Several types of parallelism can be exploited in logic programs while preserving correctness and efficiency, i.e. ensuring that the parallel execution obtains the same results as the sequential one and the amount of work performed is not greater. However, such results do not take into account a number of overheads which appear in practice, such as process creation and scheduling, which can induce a slow-down, or, at least, limit speedup, if they are not controlled in some way. This paper describes a methodology whereby the granularity of parallel tasks, i.e. the work available under them, is efficiently estimated and used to limit parallelism so that the effect of such overheads is controlled. The run-time overhead associated with the approach is usually quite small, since as much work is done at compile time as possible. Also,a number of run-time optimizations are proposed. Moreover, a static analysis of the overhead associated with the granularity control process is performed in order to decide its convenience. The performance improvements resulting from the incorporation of grain size control are shown to be quite good, specially for systems with medium to large parallel execution overheads.
Resumo:
Several models for context-sensitive analysis of modular programs have been proposed, each with different characteristics and representing different trade-offs. The advantage of these context-sensitive analyses is that they provide information which is potentially more accurate than that provided by context-free analyses. Such information can then be applied to validating/debugging the program and/or to specializing the program in order to obtain important performance improvements. Some very preliminary experimental results have also been reported for some of these models which provided initial evidence on their potential. However, further experimentation, which is needed in order to understand the many issues left open and to show that the proposed modes scale and are usable in the context of large, real-life modular programs, was left as future work. The aim of this paper is two-fold. On one hand we provide an empirical comparison of the different models proposed in previous work, as well as experimental data on the different choices left open in those designs. On the other hand we explore the scalability of these models by using larger modular programs as benchmarks. The results have been obtained from a realistic implementation of the models, integrated in a production-quality compiler (CiaoPP/Ciao). Our experimental results shed light on the practical implications of the different design choices and of the models themselves. We also show that contextsensitive analysis of modular programs is indeed feasible in practice, and that in certain critical cases it provides better performance results than those achievable by analyzing the whole program at once, specially in terms of memory consumption and when reanalyzing after making changes to a program, as is often the case during program development.
Resumo:
Several types of parallelism can be exploited in logic programs while preserving correctness and efficiency, i.e. ensuring that the parallel execution obtains the same results as the sequential one and the amount of work performed is not greater. However, such results do not take into account a number of overheads which appear in practice, such as process creation and scheduling, which can induce a slow-down, or, at least, limit speedup, if they are not controlled in some way. This paper describes a methodology whereby the granularity of parallel tasks, i.e. the work available under them, is efficiently estimated and used to limit parallelism so that the effect of such overheads is controlled. The run-time overhead associated with the approach is usually quite small, since as much work is done at compile time as possible. Also, a number of run-time optimizations are proposed. Moreover, a static analysis of the overhead associated with the granularity control process is performed in order to decide its convenience. The performance improvements resulting from the incorporation of grain size control are shown to be quite good, specially for systems with médium to large parallel execution overheads.
Resumo:
While logic programming languages offer a great deal of scope for parallelism, there is usually some overhead associated with the execution of goals in parallel because of the work involved in task creation and scheduling. In practice, therefore, the "granularity" of a goal, i.e. an estimate of the work available under it, should be taken into account when deciding whether or not to execute a goal concurrently as a sepárate task. This paper describes a method for estimating the granularity of a goal at compile time. The runtime overhead associated with our approach is usually quite small, and the performance improvements resulting from the incorporation of grainsize control can be quite good. This is shown by means of experimental results.
Resumo:
Data grid services have been used to deal with the increasing needs of applications in terms of data volume and throughput. The large scale, heterogeneity and dynamism of grid environments often make management and tuning of these data services very complex. Furthermore, current high-performance I/O approaches are characterized by their high complexity and specific features that usually require specialized administrator skills. Autonomic computing can help manage this complexity. The present paper describes an autonomic subsystem intended to provide self-management features aimed at efficiently reducing the I/O problem in a grid environment, thereby enhancing the quality of service (QoS) of data access and storage services in the grid. Our proposal takes into account that data produced in an I/O system is not usually immediately required. Therefore, performance improvements are related not only to current but also to any future I/O access, as the actual data access usually occurs later on. Nevertheless, the exact time of the next I/O operations is unknown. Thus, our approach proposes a long-term prediction designed to forecast the future workload of grid components. This enables the autonomic subsystem to determine the optimal data placement to improve both current and future I/O operations.
Resumo:
Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test–retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test–retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions.
Resumo:
Modern object oriented languages like C# and JAVA enable developers to build complex application in less time. These languages are based on selecting heap allocated pass-by-reference objects for user defined data structures. This simplifies programming by automatically managing memory allocation and deallocation in conjunction with automated garbage collection. This simplification of programming comes at the cost of performance. Using pass-by-reference objects instead of lighter weight pass-by value structs can have memory impact in some cases. These costs can be critical when these application runs on limited resource environments such as mobile devices and cloud computing systems. We explore the problem by using the simple and uniform memory model to improve the performance. In this work we address this problem by providing an automated and sounds static conversion analysis which identifies if a by reference type can be safely converted to a by value type where the conversion may result in performance improvements. This works focus on C# programs. Our approach is based on a combination of syntactic and semantic checks to identify classes that are safe to convert. We evaluate the effectiveness of our work in identifying convertible types and impact of this transformation. The result shows that the transformation of reference type to value type can have substantial performance impact in practice. In our case studies we optimize the performance in Barnes-Hut program which shows total memory allocation decreased by 93% and execution time also reduced by 15%.
Resumo:
La construcción es una de las actividades más valiosas para la sociedad debido a la naturaleza de los servicios que ofrece y por el volumen de empleos y movimiento económico que genera. Por ello es un elemento fundamental para el desarrollo sustentable. Es una industria compleja, cada vez más dependiente del conocimiento. Debido a su naturaleza fragmentaria y temporal y la alta rotación de personal presenta grandes retos y complicaciones particulares. Estas dificultades en oportunidades pueden transformarse en problemas por la complejidad, localización geográfica o los requisitos técnicos, financieros e innovaciones de los proyectos. Debido a sus características, las construcciones sufren cambios en las condiciones planificadas. Con frecuencia estos cambios conducen a retrasos en la ejecución de los proyectos, costes superiores a los presupuestados y conflictos entre los clientes y los ejecutores. Esto genera problemas de competitividad que afectan tanto a países desarrollados como países en vías de desarrollo. Los problemas de la construcción tienen perniciosos efectos para la sociedad, que pierde recursos que deberían permitir mejores resultados en términos de calidad de vida y beneficios sociales y económicos. Debido a la importancia del sector y los ingentes recursos que se invierten en cada proyecto se justifican los máximos esfuerzos para lograr los mejores desempeños de esta industria. Éste interés ha orientado el desarrollo de investigaciones, para apoyar el logro de los objetivos de mejoramiento continuo y construcción sustentable. Los estudios desarrollados han permitido demostrar el valor añadido del conocimiento en todos los sectores productivos. Para la construcción, los conocimientos ofrecen indicadores de desempeño, datos y lecciones aprendidas provenientes de aciertos y errores. Estos deben conducir a aprendizajes fundamentales para sustentar su competitividad. Sin embargo, a pesar de los conocimientos disponibles y los avances en las técnicas de control gerencial y de proyectos, es alarmante la recurrencia de los problemas de construcción. Esta problemática se manifiesta con severidad en los proyectos de construcción industrial que se desarrollan para el sector petrolero, petroquímico y energético venezolano. El sector presenta evidentes necesidades para un mejor desempeño competitivo por la alta incidencia de retrasos de los proyectos, que implican pérdidas de gran parte de los recursos humanos, financieros, técnicos y conocimientos invertidos. Esta investigación plantea como objetivos analizar la importancia de la construcción y su sustentabilidad, los principales problemas que afectan el sector, la gestión del conocimiento y algunos modelos disponibles para gestionarlos. Igualmente examina las lecciones aprendidas y la productividad y competitividad, con particular atención a los problemas de competitividad venezolanos. Adicionalmente se evalúan las implicaciones del conocimiento como activo estratégico y se caracterizan las empresas de construcción industrial venezolanas. Para ello se identifican las dimensiones que sustentan la gestión del conocimiento en estas empresas, para finalmente determinar las que resultan más idóneas para el nuevo modelo a ser propuesto. Con estos objetivos se desarrolló el estudio empírico. Para ello fueron invitados a participar representantes de 105 empresas y expertos de construcción distintos, todos con experiencias de construcción al sector industrial venezolano. Se obtuvieron 112 respuestas en representación de 41 organizaciones y expertos diferentes. El trabajo de campo inició en Junio de 2012 y culminó en Noviembre de 2012. Los datos obtenidos fueron analizados con apoyo de técnicas estadísticas descriptivas y multivariables. Los objetivos de la investigación se alcanzaron ya que se logró caracterizar el sector de las construcciones industriales y se propuso un nuevo modelo de gestión del conocimiento adecuado a sus características. El nuevo modelo fue formulado atendiendo a criterios de sencillez, bajos costes y facilidad de adaptación para motivar su utilización en organizaciones de construcción industrial variadas. Con ello se busca que resulte de utilidad aún para las organizaciones más pequeñas, con menores recursos o aquellas que enfrentan entornos constructivos complicados. Por último se presentan algunas sugerencias para motivar la comprensión de los fenómenos estudiados en los grupos de interés de la construcción. Se propone analizar estos problemas desde las etapas iniciales de los estudios de ingeniería, de arquitectura, de construcción, de economía y administración. Igualmente se propone desarrollar acciones conjuntas de parte de los sectores académicos, gubernamentales, industriales y asociaciones para el mejoramiento competitivo y desarrollo sustentable global. La propuesta aporta datos sobre el sector constructivo venezolano en un área que presenta grandes carencias y propone un modelo innovador por su sencillez y orientación hacia el uso diario e intuitivo de los conocimientos como recursos fundamentales para la competitividad. Esta orientación puede tener trascendencia más allá del sector descrito, para apoyar la solución de problemas de otras industrias en entornos globales. ABSTRACT Construction is one of the most valuable activities for society due to the nature of the services offered and the number of jobs and revenues generated. Therefore it is a key element for sustainable development. Construction is a complex industry increasingly dependent on knowledge. Its temporary and fragmentary nature and the high staff turnover present great challenges and particular complications to construction. In some cases these conditions may evolve to serious problems because of the complexity, geographic location or even technical, financial and innovative requirements of each project. Due to their characteristics, constructions frequently undergo changes in planned conditions. Often these changes lead to delays in project completion, costs higher than budgeted and conflicts between clients and performers. This creates problems of competitiveness affecting both developed and developing countries. The construction problems have harmful effects on society, since it loses resources that would otherwise allow better results in terms of quality of life and social and economic benefits. The importance and the enormous resources invested in each project justify the efforts to achieve the best performance of this industry. This interest has guided the development of multiple research efforts to support the achievement of construction performance improvements and sustainable construction. The studies carried out have demonstrated the added value of knowledge in all productive sectors. For construction, knowledge offers performance indicators, data and lessons learned from successes and failures. These should lead to fundamental learning to sustain sector competitiveness. However, despite the available knowledge and advances in techniques and project management control, the recurrence of construction problems is alarming. This problem shows itself severely in industrial construction projects that are developed for the Venezuelan oil, petrochemical and energy sectors. These sectors have evident needs for better competitive performance because of the high incidence of project delays, involving loss of much of the human, financial, technical and knowledge resources invested. This research analyzes the importance of construction and sustainability, the main problems affecting the sector, knowledge and some models available to manage them. It also examines the lessons learned and the productivity and competitiveness, with particular attention to the problems of Venezuelan competitiveness. Additionally, the Venezuelan industrial construction companies are characterized evaluating the implications of knowledge as an strategic asset for construction. Moreover, the research evaluates the dimensions that support knowledge management in these companies, to finally identify those that are the most suitable for the new model to be proposed. With these objectives in mind the empirical study was developed. 105 different companies and experts with Venezuelan industrial construction experiences were invited to participate on the survey. 112 responses were obtained representing 41 different organizations and experts. Fieldwork started in June 2012 and ended in November 2012. The data obtained was analyzed with descriptive and multivariate statistical techniques. The research objectives were achieved since the industrial construction sector was characterized and a new management model was proposed based on the particular characteristics of these companies. The new model was formulated according to the criteria of simplicity, low cost and ease of adaptation. This was performed to motivate the use of the new model in various industrial construction organizations, even in smaller companies, with limited resources or those facing complex construction environments. Finally some suggestions to encourage understanding of the phenomena studied among construction stakeholders were proposed. The importance of studying these problems at an early stage of the engineering, architectural, construction, economic and administration studies is highlighted. Additionally, academic, government, industrial organizations and associations are invited to join efforts to improve the competitive and sustainable global development. The proposal provides data on the Venezuelan construction sector in an area that has large gaps and proposes a model which is innovative for its simplicity and suggests the daily and intuitive use of knowledge resources as a key issue to competitiveness. This orientation may have implications beyond the described sector to support the solution of problems of other industries in a global environment.
Resumo:
El presente trabajo se ha centrado en la investigación de soluciones para automatizar la tarea del enriquecimiento de fuentes de datos sobre redes de sensores con descripciones lingüísticas, con el fin de facilitar la posterior generación de textos en lenguaje natural. El uso de descripciones en lenguaje natural facilita el acceso a los datos a una mayor diversidad de usuarios y, como consecuencia, permite aprovechar mejor las inversiones en redes de sensores. En el trabajo se ha considerado el uso de bases de datos abiertas para abordar la necesidad de disponer de un gran volumen y diversidad de conocimiento geográfico. Se ha analizado también el enriquecimiento de datos dentro de enfoques metodológicos de curación de datos y métodos de generación de lenguaje natural. Como resultado del trabajo, se ha planteado un método general basado en una estrategia de generación y prueba que incluye una forma de representación y uso del conocimiento heurístico con varias etapas de razonamiento para la construcción de descripciones lingüísticas de enriquecimiento de datos. En la evaluación de la propuesta general se han manejado tres escenarios, dos de ellos para generación de referencias geográficas sobre redes de sensores complejas de dimensión real y otro para la generación de referencias temporales. Los resultados de la evaluación han mostrado la validez práctica de la propuesta general exhibiendo mejoras de rendimiento respecto a otros enfoques. Además, el análisis de los resultados ha permitido identificar y cuantificar el impacto previsible de diversas líneas de mejora en bases de datos abiertas. ABSTRACT This work has focused on the search for solutions to automate the task of enrichment sensor-network-based data sources with textual descriptions, so as to facilitate the generation of natural language texts. Using natural language descriptions facilitates data access to a wider range of users and, therefore, allows better leveraging investments in sensor networks. In this work we have considered the use of open databases to address the need for a large volume and diversity of geographical knowledge. We have also analyzed data enrichment in methodological approaches and data curation methods of natural language generation. As a result, it has raised a general method based on a strategy of generating and testing that includes a representation using heuristic knowledge with several stages of reasoning for the construction of linguistic descriptions of data enrichment. In assessing the overall proposal three scenarios have been addressed, two of them in the environmental domain with complex sensor networks and another real dimension in the time domain. The evaluation results have shown the validity and practicality of our proposal, showing performance improvements over other approaches. Furthermore, the analysis of the results has allowed identifying and quantifying the expected impact of various lines of improvement in open databases.
Resumo:
During the last three decades, FPGA technology has quickly evolved to become a major subject of research in computer and electrical engineering as it has been identified as a powerful alternative for creating highly efficient computing systems. FPGA devices offer substantial performance improvements when compared against traditional processing architectures via custom design and reconfiguration capabilities.
Resumo:
Tabled evaluation has been proved an effective method to improve several aspeets of goal-oriented query evaluation, including termination and complexity. Several "native" implementations of tabled evaluation have been developed which offer good performance, but many of them need significant changes to the underlying Prolog implementation. More portable approaches, generally using program transformation, have been proposed but they often result in lower efficieney. We explore some techniques aimed at combining the best of these worlds, i.e., developing a portable and extensible implementation, with minimal modifications at the abstract machine level, and with reasonably good performance. Our preliminary results indícate promising results.
Resumo:
Gasification is a technology that can replace traditional management alternatives used up to date to deal with this waste (landfilling, composting and incineration) and which fulfils the social, environmental and legislative requirements. The main products of sewage sludge gasification are permanent gases (useful to generate energy or to be used as raw material in chemical synthesis processes), liquids (tars) and char. One of the main problems to be solved in gasification is tar production. Tars are organic impurities which can condense at relatively high temperatures making impossible to use the produced gases for most applications. This work deals with the effect of some primary tar removal processes (performed inside the gasifier) on sewage sludge gasification products. For this purpose, analysis of the gas composition, tar production, cold gas efficiency and carbon conversion were carried out. The tests were performed with air in a laboratory scale plant consisting mainly of a bubbling bed gasifier. No catalyzed and catalyzed (10% wt of dolomite in the bed and in the feeding) tests were carried out at different temperatures (750ºC, 800ºC and 850ºC) in order to know the effect of these parameters in the gasification products. As far as tars were concerned, qualitative and quantitative tar composition was determined. In all tests the Equivalence Ratio (ER) was kept at 0.3. Temperature is one of the most influential variables in sewage sludge gasification. Higher temperatures favoured hydrogen and CO production while CO2 content decreased, which might be partially explained by the effect of the cracking, Boudouard and CO2 reforming reactions. At 850ºC, cold gas efficiency and carbon conversion reached 49% and 76%, respectively. The presence of dolomite as catalyst increased the production of H2 reaching contents of 15.5% by volume at 850 °C. Similar behaviour was found for CO whereas CO2 and CnHm (light hydrocarbons) production decreased. In the presence of dolomite, a tar reduction of up to 51% was reached in comparison with no catalyzed tests, as well as improvements on cold gas efficiency and carbon conversion. Several assays were developed in order to test catalyst performance under more rough gasification conditions. For this purpose, the throughput value (TR), defined as kg sludge “as received” fed to the gasifier per hour and per m2 of cross sectional area of the gasifier, was modified. Specifically, the TR values used were 110 (reference value), 215 and 322 kg/h·m2. When TR increased, the H2, CO and CH4 production decreased while the CO2 and the CnHm production increased. Tar production increased drastically with TR during no catalysed tests what is related to the lower residence time of the gas inside the reactor. Nevertheless, even at TR=322 kg/h·m2, tar production decreased by nearly 50% with in-bed use of dolomite in comparison with no catalyzed assays under the same operating conditions. Regarding relative tar composition, there was an increase in benzene and naphthalene content when temperature increased while the content of the rest of compounds decreased. The dolomite seemed to be effective all over the range of molecular weight studied showing tar removal efficiencies between 35-55% in most cases. High values of the TR caused a significant increase in tar production but a slight effect on tar composition.
Resumo:
From the 60s to the 90s, a great number of events related to the Emergency Core Cooling Systems Strainers have been happened in all kind of reactors all over the world. Thus, the Nuclear Regulatory Commission of the USA emitted some Bulletins to address the concerns about the adequacy of Emergency Core Cooling Systems (ECCS) strainer performance at boiling water reactors (BWR). In Spain the regulatory body (Consejo de Seguridad Nuclear, CSN) adopted the USA regulation and Cofrentes NPP installed new strainers with a considerable bigger size than the old strainers. The nuclear industry conducted significant and extensive research, guidance development, testing, reviews, and hardware and procedure changes during the 90s to resolve the issues related to debris blockage of BWR strainers. In 2001 the NRC and CSN closed the Bulletins. Thereafter, the strainers issues were moved to the PWR reactors. In 2004 the NRC issued a Generic Letter (GL). It requested the resolution of several effects which were not noted in the past. The GL regarded to be resolved by the PWR reactors but the NRC in USA and the CSN in Spain have requested that the BWR reactors investigate differences between the methodologies used by the BWRs and PWRs. The developments and improvements done for Cofrentes NPP are detailed. Studies for this plant show that the head loss due to the considered debris is at most half of the limited head loss for the ECCS strainer and the NPSH (Net Positive Suction Head) required for the ECCS pumps is at least three times lower than the NPSH available.