With each technology generation we get more transistors per chip. Whilst processor frequencies have increased over the past few decades, memory speeds have not kept pace. Therefore, more and more transistors are devoted to on-chip caches to reduce latency to data and help achieve high performance. On-chip caches consume a significant fraction of the processor energy budget but need to deliver high performance. Therefore cache resources should be optimized to meet the requirements of the running applications. Fixed configuration caches are designed to deliver low average memory access times across a wide range of potential applications. However, this can lead to excessive energy consumption for applications that do not require the full capacity or associativity of the cache at all times. Furthermore, in systems where the clock period is constrained by the access times of level-1 caches, the clock frequency for all applications is effectively limited by the cache requirements of the most demanding phase within the most demanding application. This motivates the need for dynamic adaptation of cache configurations in order to optimize performance while minimizing energy consumption, on a per-application basis. First, this thesis proposes an energy-efficient cache architecture for a single core system, along with a run-time support framework for dynamic adaptation of cache size and associativity through the use of machine learning. The machine learning model, which is trained offline, profiles the application’s cache usage and then reconfigures the cache according to the program’s requirement. The proposed cache architecture has, on average, 18% better energy-delay product than the prior state-of-the-art cache architectures proposed in the literature. Next, this thesis proposes cooperative partitioning, an energy-efficient cache partitioning scheme for multi-core systems that share the Last Level Cache (LLC), with a core to LLC cache way ratio of 1:4. The proposed cache partitioning scheme uses small auxiliary tags to capture each core’s cache requirements, and partitions the LLC according to the individual cores cache requirement. The proposed partitioning uses a way-aligned scheme that helps in the reduction of both dynamic and static energy. This scheme, on an average offers 70% and 30% reduction in dynamic and static energy respectively, while maintaining high performance on par with state-of-the-art cache partitioning schemes. Finally, when Last Level Cache (LLC) ways are equal to or less than the number of cores present in many-core systems, cooperative partitioning cannot be used for partitioning the LLC. This thesis proposes a region aware cache partitioning scheme as an energy-efficient approach for many core systems that share the LLC, with a core to LLC way ratio of 1:2 and 1:1. The proposed partitioning, on an average offers 68% and 33% reduction in dynamic and static energy respectively, while again maintaining high performance on par with state-of-the-art LLC cache management techniques.

Energy consumption has become a major research topic from both environmental and economical perspectives. The telecommunications industry is currently responsible for 0.7% of the total global carbon emissions, a figure which is increasing at rapid rate. By 2020, it is desired that CO2 emissions can be reduced by 50%. Thus, reducing the energy consumption in order to lower carbon emissions and operational expenses has become a major design constraint for future communication systems. Therefore, in this thesis energy efficient resource allocation methods have been studied taking the Long Term Evolution (LTE) standard as an example. Firstly, a theoretical analysis, that shows how improvements in energy efficiency can directly be related with improvements in fairness, is provided using a Shannon theory analysis. The traditional uplink power control challenge is re-evaluated and investigated from the view point of interference mitigation rather than power minimization. Thus, a low complexity distributed resource allocation scheme for reducing the uplink co-channel interference (CCI) is presented. Improvements in energy efficiency are obtained by controlling the level of CCI affecting vulnerable mobile stations (MSs). This is done with a combined scheduler and a two layer power allocation scheme, which is based on non-cooperative game theory. Simulation results show that the proposed low complexity method provides similar performance in terms of fairness and energy efficiency when compared to a centralized signal interference noise ratio balancing scheme. Apart from using interference management techniques, by using efficiently the spare resources in the system such as bandwidth and available infrastructure, the energy expenditure in wireless networks can also be reduced. For example, during low network load periods spare resource blocks (RBs) can be allocated to mobile users for transmission in the uplink. Thereby, the user rate demands are split among its allocated RBs in order to transmit in each of them by using a simpler and more energy efficient modulation scheme. In addition, virtual Multiple-input Multiple-output (MIMO) coalitions can be formed by allowing single antenna MSs and available relay stations to cooperate between each other to obtain power savings by implementing the concepts of spatial multiplexing and spatial diversity. Resource block allocation and virtual MIMO coalition formation are modeled by a game theoretic approach derived from two different concepts of stable marriage with incomplete lists (SMI) and the college admission framework (CAF) respectively. These distributed approaches focus on optimizing the overall consumed power of the single antenna devices rather than on the transmitted power. Moreover, it is shown that when overall power consumption is optimized the energy efficiency of the users experiencing good propagation conditions in the uplink is not always improved by transmitting in more than one RB or by forming a virtual MIMO link. Finally, it is shown that the proposed distributed schemes achieve a similar performance in bits per Joule when compared to much more complex centralized resource allocation methods.

Independent metering poses a possibility to improve energy efficiency of throttlecontrolled hydraulic single-rod cylinder drives. This paper deals with energetic potentials gained through variable circuitry that come along with independent metering. A method to assess energetic potentials is described, based on load specific, optimal operating modes. As a means of yielding maximum energy efficiency for a wide range of applications, a smooth mode switching algorithm that minimizes losses and allows good motion tracking is proposed. The mode switching algorithm is validated in simulation and on a test stand.

Pneumatic linear drives are widely used in manufacturing, mainly for handling tasks. Due to rising interest in environmental matters and increasing energy costs, energy efficiency has become a major issue in industrial applications. There is a growing competition between pneumatic and electromechanical drives. Pneumatic drives are said to have a lower efficiency while the initial costs of electromechanical drives are higher. The operating costs of electromechanical as well as pneumatic drives are induced by their exergy efficiency. The efficiency of the drives depends on parameters like cycle time, load applied to the cylinder and its acceleration and velocity. Former research did only provide limited data on the influence of these parameters. The paper provides an overview on the exergy efficiency of pneumatic and electromechanical drives and its dependency on the mentioned parameters. Since electromechanical drives are often used to replace pneumatic drives both technologies are examined in typical applications for pneumatic drives, including horizontal and vertical movement and sustaining a load for different periods in vertical usage.

The objective of this thesis is to model and analyze the energy consumption in heterogeneous cellular systems and develop techniques to minimize it. First, the energy consumption is modeled and analyzed for multi-layered heterogeneous wireless systems. This work encompasses the characterization of all the energy consumed at the base stations. Then, a novel on-off and cell-association scheme is proposed to minimize the overall network energy consumption while satisfying the spatially- and temporally-varying traffic demands. Second, we exploit the use of multi-stream carrier aggregation not only to improve the energy efficiency, but also to balance it with the conflicting objective of capacity maximization. Third, we analyze the performance of discontinuous reception methods for energy savings within the user equipments. Then, for scenarios that support carrier aggregation, we develop a cross-carrier-aware technique that further enhances such savings with minimum impact on the packet delay. Fourth, the use of small cells as an energy-saving tool and its limitations are analyzed and modeled in OPNET, a high-fidelity simulation and development platform. To bypass such limitations, a novel small cell solution is proposed, modeled, and analyzed in OPNET and then compared against its existing alternative.

The objective of this research is to characterize and manage lifetime reliability, microarchitectural performance, and power tradeoffs in multicore processors. This dissertation is comprised of three research themes; 1) modeling and simulation method of interacting multicore processor physics, 2) characterization and management of performance and lifetime reliability tradeoff, and 3) extending Amdahl’s Law for understanding lifetime reliability, performance, and energy efficiency of heterogeneous processors. With continued technology scaling, processor operations are increasingly dominated by multiple distinct physical phenomena and their coupled interactions. Understanding these behaviors requires the modeling of complex physical interactions. This dissertation first presents a novel simulation framework that orchestrates interactions between multiple physical models and microarchitecture simulators to enable research explorations at the intersection of application, microarchitecture, energy, power, thermal, and reliability. Using this framework, workload-induced variation of device degradation is characterized, and its impacts on processor lifetime and performance are analyzed. This research introduces a new metric to quantify performance-reliability tradeoff. Lastly, the theoretical models of heterogeneous multicore processors are proposed for understanding performance, energy efficiency, and lifetime reliability consequences. It is shown that these system metrics are governed by Amdahl’s Law and correlated as a function of processor composition, scheduling method, and Amdahl’s scaling factor. This dissertation highlights the importance of multidimensional analysis and extends the scope of microarchitectural studies by incorporating the physical aspects of processor operations and designs.

Concerns about global warming are increasing, hence, the urgency to cut carbon emissions. Reducing energy consumption, including lighting energy, is seen as the primary solution. Yet, solving the environmental factor should not come at the cost of other pillars of sustainable development. Rather, maximizing the total value of the building should be the focus. Maximizing value in the context of lighting entails improving the quality of the lighting. This study has investigated how lighting simulation could help in achieving better lighting quality. The aim of the thesis was defined as to understand the underlying architecture of lighting simulation and obtain an overview of its characteristics and applications as well as to study the use of current simulation tools. The theoretical background of lighting simulation (in the domain of Systems Engineering) was reviewed from the literature. This revealed the missing and imperfect links in the solution-to-value chain. The thesis suggests the use of a new base metric, Retinal Illuminance Map, as a solution, which in combination with black box simulation of a visual system can help repair this incomplete chain. The study of the current lighting simulation tools (Paper 1) revealed that illuminance-based metrics, luminance-based metrics, daylight availability metrics, and glare indexes are the most available performance metrics in existing lighting simulation tools. Based on usability, acceptability, availability, and previous references in the literature six software programs (Radiance, DAYSIM, Evalglare, DIALux, VELUX, and VISSLA) were selected and compared. It was found that no single tool could meet all the needs of a designer, hence, simulation tool(s) should be selected (or combined) according to the requirements of project goals and the stage of design. Building on these studies, applications of lighting simulation were identified and compiled in relation to different aspects, including performance metrics, stages of design, optimization, model integration, BIM, and parametric modeling. To obtain first-hand information about lighting designers’ experience, an online survey was conducted in Sweden (Paper 2). The results showed that lighting simulation programs were widely (90%) used in Sweden for analysis and/or rendering purposes. The majority of lighting designers considered both daylight and artificial light in their design. Factors such as ease-of use, simulation time and training had more weight than accuracy and the diversity of metrics in practitioner’s eyes. Surrogate modeling was identified as a solution for speeding up simulation time, which would also enable exploration of design solution space especially in the early design stage.

<p>U radu je izvr&scaron;ena detaljna analiza uticajnih faktora na energetsku efikasnost prijemnika sunčeve energije u dinamičkim uslovima rada. Identifikovani su parametri koji utiču na povećanje efikasnosti reprezentativnih tipova prijemnika koji se nalaze u komercijalnoj primeni. Promenom geometrijskih parametara konstrukcije i radnih parametara utvrđen je njihov uticaj na energetsku efikasnost a zatim je kreiran model za ocenu povećanja efikasnosti prijemnika sunčeve energije u dinamičkim uslovima rada.</p>

Predation, density and disease affect behavior, morphology and growth. There is a lack of information on how these changes relate to efficiency of energy transfer in anuran larvae, although previous studies suggest that predation should decrease and competition should increase efficiency. Using a 2 x 2 factorial design, we manipulated predation presence and larval density to test how predation risk and density affect energy efficiency. During the experiment, approximately half of the tadpoles were infected by an unknown disease. Neither predation risk nor density affected assimilation or growth efficiency, despite changes in growth and development. Disease, however, decreased gut length and growth efficiency. This study builds on past work on the effects of predation and density on a larval amphibian, but also introduces disease as another factor. Our study suggests that disease may be at least as important if not more important than predation or density in regards to growth efficiency.

As part of an effort to be a world leader in international efforts in reducing atmospheric carbon dioxide levels, the UK Government has set itself ambitious targets to reduce carbon dioxide emissions by 80% relative to 1990 levels by 2050. To meet this target, there is a strong emphasis in reducing carbon emissions from the domestic sector through the reduction of energy consumption in UK households by improving the energy efficiency of the housing stock, and the behaviours of the occupants. The Department of Energy and Climate Change have indicated that Local Authorities in England are potentially to work in partnership with businesses and community organizations to facilitate delivery; and as a promoter of domestic energy efficiency policies. Consultation with 11 Local Authorities across England confirmed that they are lacking a reliable mechanism that can detect areas within their administrative boundaries that are most in need of intervention to improve the energy efficiency of the housing stock. For the year 2008 the regression models demonstrate that geographical variations in the size of the house, median household income, and air temperature account for 64% of the variation in English domestic gas consumption, and that variations in the size of the house, median household income, and proportion of households connected to the national gas grid account for 73% of the variation in domestic electricity consumption. The predicted values from these regression models serve as benchmarks of domestic gas and electricity consumption in England having accounted for household income, house size, house type, tenure, and climatic differences and could be used to identify areas within Local Authorities with higher than expected energy consumption for energy efficiency interventions. These results contribute to the wider academic debate over how best to achieve the overall aims of household CO2 reductions by moving beyond a purely technical or behavioural-based approach to reducing domestic energy consumption.