Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-04-13T12:23:40Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) DISSERTAÇÃO CORRIGIDA E IMPRESSA.pdf: 8529514 bytes, checksum: 22404f929127279cf0e8547f5c3df094 (MD5) / Made available in DSpace on 2016-04-13T12:23:40Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) DISSERTAÇÃO CORRIGIDA E IMPRESSA.pdf: 8529514 bytes, checksum: 22404f929127279cf0e8547f5c3df094 (MD5) Previous issue date: 2015-08-14 / CNPq / O elevado consumo de energia para climatização das edificações tem motivado a realização de muitos trabalhos de pesquisa na área de eficiência energética. Os telhados das construções, em particular, são responsáveis por uma grande parcela do consumo de energia para aquecimento ou refrigeração. Os telhados dos galpões industriais, por serem de grandes extensões, são os principais meios de absorção energética advinda da radiação solar durante os dias, em especial, os dias de verão. Este trabalho apresenta um modelo, desenvolvido em Matlab, que parte do balanço de energia para a superfície do telhado e resolução do mesmo por meio de equações consolidadas da literatura científica, considerando dados de radiação solar incidente e influências da longitude e latitude locais. Com isto, objetiva-se determinar o aquecimento sofrido por cada tipo de telhado analisado e o fluxo de calor que atravessa os mesmos, a fim de que se possa inferir qual telhado possui maior eficiência energética para cada região do país. Foram analisados 4 tipos de telhado, com e sem revestimento reflexivo e isolamento térmico. Constatou-se que tanto as aplicações do isolamento térmico quanto do revestimento reflexivo proporcionam redução do fluxo para o interior dos edifícios, ocasionando melhorias no desempenho térmico dos mesmos. / The high energy consumption for air conditioning of buildings has motivated the implementation of many research papers in the area of energy efficiency. The roofs of buildings, in particular, account for a large share of energy consumption for heating or cooling. The roofs of industrial buildings, because they are large areas, are the main means of energy absorption arising from solar radiation during the day, especially the summer days. This paper presents a model, developed in Matlab, that part of the energy balance for the roof surface and resolution through consolidated equations of scientific literature, considering data of solar radiation and influences the longitude and latitude locations. With this, the objective is to determine the heating suffered by each type of roof and analyzed the heat flow through them, so that one can infer what roof has greater energy efficiency for each region of the country. 4 roof types were analyzed with and without reflective coating and thermal insulation. It was found that both the thermal insulation applications as reflective coating provide the reduction in flow to the interior of buildings, resulting in improved thermal performance thereof.

Phase Change Materials have been the subject of increased research in modern times. Phase Change Materials, abbreviated as PCMs, are being used in a variety of applications in the energy conservation world. In this study, the effect of PCMs on a residential building’s energy consumption was evaluated at different locations across the United States and compared to the standard building at the same locations. An average American residential building was designed and modeled in SketchUp software. The building was evaluated for energy consumption at different locations across the United States using weather data for each chosen location. After the baseline results were collected, the building was re-evaluated, under the same conditions, with a Heptadecane embedded in the exterior walls as the chosen PCM for this study. The results of this study show that Phase Change Materials have a wide-ranging effect on the energy consumption of the designed building. Addition of the PCM to the building walls decreased total energy usage, over the course of a year, by 3.02 – 6.72%, depending on the location.

The importance of energy conservation in all the aspects of energy production, transportation, distribution and utilisation should not be underestimated. A special attention to that is paid since the oil crisis in 70’s of the last century. Today energy efficiency has increased considerably, but there is still a potential for energy savings. This potential is widely spread in power plants, energy supply systems, factories, plants, agricultural and residential facilities.   In the countries in transition, such as former socialist countries, energy saving policies have started not so long time ago and a lot of work is to be done in order to improve energy efficiency and approach the level of developed countries. In Moldova, the energy sector is one of the most problematic parts of the national economy. 98% of the primary energy resources are imported, which complicates very much energy security in the state. Some internal problems, such as lack of investments in the sector, old and inefficient facilities, uncontrolled and unpaid energy consumption, internal social and political instability create additional difficulties in improving this situation. Industry and residential sector consume the highest amount of the supplied energy. It is obvious that improved energy efficiency in these sectors could lead to big energy savings. Reduction in energy consumption will favourably influence the impact of the energy sector on the environment.   The present work aims at identifying energy saving potential in the industrial and residential facilities in Moldova. Interdependence between energy and environment, the positive influence of reduced energy consumption on the environment is shown. Future development strategies and energy resources potential are also discussed.   A brief history overview of Moldova and of the energy sector development are presented for a better understanding of the particularities and reasons of the present situation. This is followed by a description of the energy sector in Moldova, its infrastructure and economy, the problems to pass and energy security objectives. In the following part, energy and environment issues are discussed and the way energy conservation influences environmental impact. Environmental aspects of energy use, policy, legislation and institutions in Moldova are also described. Energy Conservation Programme is presented concluding this part.   Energy utilisation sector, with deeper analysis of industrial and residential parts is overviewed in the main part of the study. Energy conservation measures are discussed in case studies and the energy savings potential is shown.   Scenarios and strategies for future development of the energy system of Moldova are described as a result of the study. Conclusions and further work suggestions are made.

To address the ever-increasing demand for computing capacities, more and more heterogeneous systems have been designed to use both general-purpose and special-purpose processors. The huge energy consumption of them raises new environmental concerns and challenges. Besides performance, energy efficiency is another key factor to be considered by system designers and consumers. In particular, contemporary graphics processing units (GPUs) support dynamic voltage and frequency scaling (DVFS) to balance computational performance and energy consumption. However, accurate and straightforward performance and power estimation for a given GPU kernel under different frequency settings is still lacking for real hardware, which is essential to determine the best frequency configuration for energy saving. In this thesis, we investigate how to improve the energy efficiency of GPU systems by accurately modeling the effects of GPU DVFS on the target GPU kernel. We also propose efficient algorithms to solve the communication contention problem in scheduling multiple distributed deep learning (DDL) jobs on GPU clusters. We introduce our studies as follows. First, we present a benchmark suite EPPMiner for evaluating the performance, power, and energy of different heterogeneous systems. EPPMiner consists of 16 benchmark programs that cover a broad range of application domains, and it shows a great variety in the intensity of utilizing the processors. We have implemented a prototype of EPPMiner that supports OpenMP, CUDA, and OpenCL, and demonstrated its usage by three showcases. The showcases justify that GPUs provide much better energy efficiency than other types of computing systems, and especially illustrate the effectiveness of GPU Dynamic Voltage and Frequency Scaling (DVFS) on the energy efficiency of GPU applications. Second, we reveal a fine-grained analytical model to estimate the execution time of GPU kernels with both core and memory frequency scaling. Compared to the cycle-level simulators, which are too slow to apply on real hardware, our model only needs one-off micro-benchmarks to extract a set of hardware parameters and kernel performance counters without any source code analysis. Our experimental results show that the proposed performance model can capture the kernel performance scaling behaviors under different frequency settings and achieve decent accuracy. Third, we design a cross-benchmarking suite, which simulates kernels with a wide range of instruction distributions. The synthetic kernels generated by this suite can be used for model pre- training or as supplementary training samples. We then build machine learning models to predict the execution time and runtime power of a GPU kernel under different voltage and frequency settings. Validated on three modern GPUs with a wide frequency scaling range, by using a collection of 24 real application kernels, the model trained only with our cross-benchmarking suite is able to achieve considerably accurate results. At last, we establish a new DDL job scheduling framework which organizes DDL jobs as Directed Acyclic Graphs (DAGs) and considers communication contention between nodes. We then propose an efficient job placement algorithm, Least-Workload-First- (LWF-), to balance the GPU utilization and consolidate the allocated GPUs for each job. When scheduling the communication tasks, we propose Ada-SRSF for the DDL job scheduling problem to address the communication contention issue. Our simulation results show that LWF- achieves up to 1.59x improvement over the classical first-fit algorithms. More importantly, Ada-SRSF reduces the average job completion time by up to 36.7%, as compared to the solutions of either avoiding all the communication contention or accepting all of it

To address the ever-increasing demand for computing capacities, more and more heterogeneous systems have been designed to use both general-purpose and special-purpose processors. The huge energy consumption of them raises new environmental concerns and challenges. Besides performance, energy efficiency is another key factor to be considered by system designers and consumers. In particular, contemporary graphics processing units (GPUs) support dynamic voltage and frequency scaling (DVFS) to balance computational performance and energy consumption. However, accurate and straightforward performance and power estimation for a given GPU kernel under different frequency settings is still lacking for real hardware, which is essential to determine the best frequency configuration for energy saving. In this thesis, we investigate how to improve the energy efficiency of GPU systems by accurately modeling the effects of GPU DVFS on the target GPU kernel. We also propose efficient algorithms to solve the communication contention problem in scheduling multiple distributed deep learning (DDL) jobs on GPU clusters. We introduce our studies as follows. First, we present a benchmark suite EPPMiner for evaluating the performance, power, and energy of different heterogeneous systems. EPPMiner consists of 16 benchmark programs that cover a broad range of application domains, and it shows a great variety in the intensity of utilizing the processors. We have implemented a prototype of EPPMiner that supports OpenMP, CUDA, and OpenCL, and demonstrated its usage by three showcases. The showcases justify that GPUs provide much better energy efficiency than other types of computing systems, and especially illustrate the effectiveness of GPU Dynamic Voltage and Frequency Scaling (DVFS) on the energy efficiency of GPU applications. Second, we reveal a fine-grained analytical model to estimate the execution time of GPU kernels with both core and memory frequency scaling. Compared to the cycle-level simulators, which are too slow to apply on real hardware, our model only needs one-off micro-benchmarks to extract a set of hardware parameters and kernel performance counters without any source code analysis. Our experimental results show that the proposed performance model can capture the kernel performance scaling behaviors under different frequency settings and achieve decent accuracy. Third, we design a cross-benchmarking suite, which simulates kernels with a wide range of instruction distributions. The synthetic kernels generated by this suite can be used for model pre- training or as supplementary training samples. We then build machine learning models to predict the execution time and runtime power of a GPU kernel under different voltage and frequency settings. Validated on three modern GPUs with a wide frequency scaling range, by using a collection of 24 real application kernels, the model trained only with our cross-benchmarking suite is able to achieve considerably accurate results. At last, we establish a new DDL job scheduling framework which organizes DDL jobs as Directed Acyclic Graphs (DAGs) and considers communication contention between nodes. We then propose an efficient job placement algorithm, Least-Workload-First- (LWF-), to balance the GPU utilization and consolidate the allocated GPUs for each job. When scheduling the communication tasks, we propose Ada-SRSF for the DDL job scheduling problem to address the communication contention issue. Our simulation results show that LWF- achieves up to 1.59x improvement over the classical first-fit algorithms. More importantly, Ada-SRSF reduces the average job completion time by up to 36.7%, as compared to the solutions of either avoiding all the communication contention or accepting all of it

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH. / Includes bibliographical references (leaves 160-167). / Historically, atria were protected interior patios; well perceived for their climate tempering and spatial amenity to the building; matching a peaceful private outdoor with the yearly climate cycles. Public buildings adopted this in larger scale, and with the ending 18th century, atria and arcades merged to a period of architectural highlights of glass covered interiors in steel and glass. Passages, hotels and public buildings of an emerging industrial society in Europe and Northern States spurred the evolution of the "Great Indoors" as an urban feature. The ecology of these indoors were consciously achieved by passive means of temperature control. With the rise of mechanical conditioning and excessive use of glass at facades by the beginning of this century, atria and arcades disappeared more or less from the architectural vocabulary. The late 1950s though experienced a revival of atria as a commercial amenity in malls, hotels and similar type of public places. These atria, however, were generally mechanical conditioned; just typically being enormous energy wasters. With the growing urge for energy conservation today, new parameters form our buildings. For this, atria and arcades of urban scale and passive control achieve a new validity as energy conscious urban form. As the key to our energy future in buildings lies well in the urban context, whose inventory per se offers already a fair degree of energy efficiency, improvements there would yield greatest rewards compared to current suburban solar sprawl. The re-interpretation of atria and arcades will provide a perfect planning tool for this urban energy conservation. The glass covered indoors will match with urban scale and site restraints and spur urban life for livable norther winter cities. Exploring atria and arcades as climate buffers and interior amenity for snow belt latitudes, this thesis presents an architectural review, and concludes with design patterns for habitable and energy conscious urban indoors. / by Joachim W. Glässel. / M.S.

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A cogeneration system using a noncondensing steam turbine to simultaneously provide electricity and process steam to a citrus plant was modeled in order to assess the source energy savings and the economic implications with the employment of this type system under conditions of time varying plant energy demand. Average monthly energy demand data from on citrus plant was analyzed. It was determined that the important parameter, in addition to a minimum demand level, for assessing economic acceptability is the demand thermal to electric ratio. One set of steam conditions will not necessarily provide the maximum source energy savings and at the same time be the most economically beneficial. The values of the economic criteria will remain relatively constant over a range of rated turbine capacities for each set of steam conditions.