Substantial Energy Efficiency Research Articles

Green Rate‐Splitting Multiple Access for Multicell and Rate Fairness Maximization

ABSTRACTThis paper investigates the green design of rate‐splitting multiple access (RSMA) for multicell, multiantenna downlink communication systems to maximize rate fairness under quality of service (QoS) constraints. An optimization framework is developed to minimize the weighted sum power consumption by jointly optimizing transmit beamformers, power allocation, and common/private rate split while ensuring per‐user minimum rate requirements. The algorithm design explicitly considers the rate fairness among users via a newly proposed green fairness index. The nonconvex transceiver design problems are transformed into tractable forms and efficiently solved by applying tools from alternating optimization and successive convex approximation. Extensive simulations demonstrate that the proposed green RSMA optimization framework can effectively balance the throughput among cell‐edge and cell‐center users, hence combating the near‐far effect. Simulation results show that at 20‐dB SNR, green RSMA achieves over 20% and 50% sum rate improvement compared with NOMA and OMA, respectively. Moreover, green RSMA maintains high fairness among users, even when the channel conditions are disparate. When the weakest user is located 120 m from the base station, green RSMA exhibits a 21.2% higher fairness index than NOMA, showcasing its ability to ensure equitable service quality across users. The framework also achieves substantial energy efficiency gains, consuming less power while providing higher data rates than baseline schemes. These results demonstrate the effectiveness of green RSMA in enhancing spectral efficiency, user fairness, and energy efficiency in multicell, multiantenna communication systems, making it a promising solution for sustainable and high‐performance wireless networks.

Understanding users of online energy efficiency counseling: comparison to representative samples in Norway.

To achieve substantial energy efficiency improvements in the privately owned building stock, it is important to communicate with potential renovators at the right point in time and provide them with targeted information to strengthen their renovation ambitions. The European Union recommends using one-stop-shops (OSSs), which provide information and support throughout the whole process, from planning to acquisition of funding, implementation, and evaluation as a measure to remove unnecessary barriers. For this paper, we invited visitors of two Norwegian websites with OSS characteristics to answer an online survey about their renovation plans and energy efficiency ambitions. The participants visited the websites out of their own interest; no recruitment for the websites was conducted as part of the study (N = 437). They also rated a range of psychological drivers, facilitators, and barriers to including energy upgrades in a renovation project. Their answers were then compared to existing data from representative samples of Norwegian households regarding home renovation in 2014, 2018, and 2023, as well as data from a sample of people who were engaged in renovation projects in 2014, which was collected by the research team with a similar online survey. Furthermore, 78 visitors completed a brief follow-up online survey one year later to report the implemented measures. We found that visitors of the websites are involved in more comprehensive renovation projects and have substantially higher ambitions for the upgrade of energy efficiency compared to the representative samples. They also perceive stronger personal and social norms, as well as have a different profile of facilitators and barriers. The findings suggest to policymakers that OSSs should be marketed especially to people motivated to upgrade energy efficiency but lack information and are unable to implement their plans alone. Also, the construction industry might refer interested people to such low-threshold online solutions to assist informed and more ambitious decisions.

Sustainable approach to integrate a conventional power plant and renewable energies, coupled with the Goswami cycle and Maisotsenko heat exchanger

AbstractThis paper presents a pioneering investigation into an integrated power generation cycle that combines gas turbines, steam turbines, Goswami cycles, biomass fuel, solar energy sources, and advanced Maisotsenko heat exchangers. Biomass gasification has been applied to partially fuel the gas turbine, while the M‐Cycle serves as the gas turbine inlet air cooling system. Solar parabolic collectors are utilized to elevate the compressed air temperature for combustion, and the Goswami cycle generates both power and cooling through waste heat recovery. This research addresses a critical gap by undertaking a holistic examination of the integrated power generation cycle, modelling the overall system performance by considering interactions and synergies between various components. The base model has been implemented, and the impacts of influential parameters on system efficiency, such as ambient temperature, seasonal variation, and steam‐to‐biomass ratio, have been taken into consideration. Remarkably, the incorporation of the M‐Cycle, solar parabolic systems, steam cycles, and the Goswami cycle into the base gas cycle results in substantial energy efficiency enhancements of 1.59%, 1.96%, 16.87%, and 6.06%, respectively, highlighting the transformative potential of this integrated approach for sustainable and efficient power generation.

NimbleChain: Speeding up Cryptocurrencies in General-purpose Permissionless Blockchains

Nakamoto’s seminal work gave rise to permissionless blockchains, as well as a wide range of proposals to mitigate their performance shortcomings. Despite substantial throughput and energy efficiency achievements, most proposals only bring modest (or marginal) gains in transaction commit latency. Consequently, commit latencies in today’s permissionless blockchain landscape remain prohibitively high. This article proposes NimbleChain, a novel algorithm that extends permissionless blockchains based on Nakamoto consensus with a fast path that delivers causal promises of commitment or simply promises . Since promises only partially order transactions, their latency is only a small fraction of the totally ordered commitment latency of Nakamoto consensus. Still, the weak consistency guarantees of promises are strong enough to correctly implement cryptocurrencies. To the best of our knowledge, NimbleChain is the first system to bring together fast, partially ordered transactions with consensus-based, totally ordered transactions in a permissionless setting. This hybrid consistency model is able to speed up cryptocurrency transactions while still supporting smart contracts, which typically have (strong) sequential consistency needs. We implement NimbleChain as an extension of Ethereum and evaluate it in a 500-node geo-distributed deployment. The results show NimbleChain can promise a cryptocurrency transactions up to an order of magnitude faster than a vanilla Ethereum implementation, with marginal overheads.

A 16-nm 784-Core Digital Signal Processor Array, Assembled as a 2 × 2 Dielet With 10-μm Pitch Interdielet I/O for Runtime Multiprogram Reconfiguration

Modern applications require hardware accelerators to maintain energy efficiency while satisfying the increasing computation requirements. However, with evolving standards and rapidly changing algorithmic complexity as well as rising design costs at advanced technology nodes, the iterative development of inflexible accelerators for such applications becomes ineffective. The reconfigurable architectures can provide a higher throughput and the required flexibility, but with substantial energy and area efficiency overhead relative to the accelerators. We develop a domain-specific, energy- and area-efficient (within 2× - 10× of accelerators) multiprogram runtime reconfigurable accelerator called the universal digital signal processor (UDSP). The design maximizes generality and resource utilization for signal processing and linear algebra with minimal area and energy penalty. The statistics-driven multilayer network minimizes the network delay and consists of an optimized switchbox design that maximizes the connectivity per hardware cost. The multilayered interconnect network is linearly scalable with the number of processing elements and allows for intradielet and multidielet scaling. The network features’ deterministic routing and timing for fast program compile and its translation and rotation symmetries allow for hardware resource reallocation. Multidielet scaling is enabled by energy-efficient, high-bandwidth, and high-density interdielet communication channels that seamlessly extend the intradielet routing network across the dielet boundaries using 10- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> fine-pitch silicon interconnect fabric (Si-IF) interposer. A 2 × 2 multidielet UDSP on Si-IF can achieve a peak energy efficiency of 785 GMACs/J at 0.42 V and 315 MHz. The interdielet communication channel, SNR-10, provides a shoreline bandwidth density of 297 Gb/s/mm at 1.1 Gb/s/pin at 0.8 V and nominal energy efficiency of 0.38 pJ/bit.

Low Energy Switching of Phase Change Materials Using a 2D Thermal Boundary Layer.

The switchable optical and electrical properties of phase change materials (PCMs) are finding new applications beyond data storage in reconfigurable photonic devices. However, high power heat pulses are needed to melt-quench the material from crystalline to amorphous. This is especially true in silicon photonics, where the high thermal conductivity of the waveguide material makes heating the PCM energy inefficient. Here, we improve the energy efficiency of the laser-induced phase transitions by inserting a layer of two-dimensional (2D) material, either MoS2 or WS2, between the silica or silicon substrate and the PCM. The 2D material reduces the required laser power by at least 40% during the amorphization (RESET) process, depending on the substrate. Thermal simulations confirm that both MoS2 and WS2 2D layers act as a thermal barrier, which efficiently confines energy within the PCM layer. Remarkably, the thermal insulation effect of the 2D layer is equivalent to a ∼100 nm layer of SiO2. The high thermal boundary resistance induced by the van der Waals (vdW)-bonded layers limits the thermal diffusion through the layer interface. Hence, 2D materials with stable vdW interfaces can be used to improve the thermal efficiency of PCM-tuned Si photonic devices. Furthermore, our waveguide simulations show that the 2D layer does not affect the propagating mode in the Si waveguide; thus, this simple additional thin film produces a substantial energy efficiency improvement without degrading the optical performance of the waveguide. Our findings pave the way for energy-efficient laser-induced structural phase transitions in PCM-based reconfigurable photonic devices.

FCNNLib: A Flexible Convolution Algorithm Library for Deep Learning on FPGAs

Convolution features huge complexity and demands high computation capability. Among hardware platforms, field programmable gate array (FPGA) emerges as a promising solution for its substantial available parallelism and energy efficiency. Besides, convolution can be implemented with different algorithms, including conventional, general matrix–matrix multiplication (GEMM), Winograd, and fast Fourier transformation (FFT) algorithms, which are diverse in arithmetic complexity, resource requirement, etc. Different convolutional neural network (CNN) models have different topologies and structures, favoring different convolution algorithms. In response, software libraries such as cuDNN provide a variety of computational primitives to support these algorithms. However, supporting such libraries on FPGAs is challenging. First, multiple algorithms can share the FPGA resources spatially as well as temporally, introducing either reconfiguration overhead or resource underutilization. Second, FPGA implementation remains a significant challenge for library developers. It typically requires significant specialized hardware knowledge. In this article, we propose <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FCNNLib</monospace> , an efficient and scalable convolution algorithm library on FPGAs. To coordinate multiple convolution algorithms on FPGAs, we develop three schedulings: 1) spatial; 2) temporal; and 3) hybrid, which exhibit different tradeoffs in latency and throughput. We explore these schedulings by balancing the reconfiguration overhead, resource utilization, and optimization objectives of the CNNs. Then, we provide efficient and tunable algorithm templates that allow performance tuning through performance and resource models. To arm the users, <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FCNNLib</monospace> exposes a set of interfaces to support high-level application designs. We demonstrate the usability of <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FCNNLib</monospace> with state-of-the-art CNNs. <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FCNNLib</monospace> achieves up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$44.6\times $ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.76\times $ </tex-math></inline-formula> energy efficiency in various scenarios compared with software libraries for CPUs and GPUs, respectively.

Design optimization of smart glazing optical properties for office spaces

In this paper, a systematic analysis is presented to determine optimal optical properties of smart glazing to minimize energy demand for perimeter office spaces. The optimization analysis considers the impacts of design and operation conditions of commercial buildings including size and orientation of windows as well as the climate characteristics of the buildings. In addition, daylighting benefits are included in the analysis of smart glazing that can transition between clear and dark states as well as intermediate tint levels. The optimization analysis results confirm that smart glazing can provide substantial energy efficiency for office buildings when coupled with daylighting controls especially for cold climates and large windows. However, the analysis indicates that specific set of optical properties for both clear and dark states are required to achieve optimal energy efficiency benefits for smart glazing when applied to office spaces. Indeed, the presented analysis allows the identification of the optimal optical properties for smart glazing depending on several influencing factors including primarily the climate as well as the window size and orientation. Moreover, the magnitude of the annual energy savings achieved by the smart glazing depends largely on the optical properties of the static glazing type used as a reference. Using code-compliant static glazing as a reference, the energy savings incurred by smart glazing range from 1.2% to 13.3% depending on daylighting controls and climatic conditions.

Iot based Fire and Gas monitoring System

In infrastructure and industrial plants the rapid growth is creating environmental issues like pollution, climate change and malfunctioning. It has a great consequence for the requirement of an operationally adaptable, efficient, cheap and smart monitoring systems. For this purpose we come up with idea to use these kind of technology i.e the Internet of Things (IoT) in form of a solution. In this paper, we suggest wireless data gathering frameworks that enable each detector node to track the changes in the behavioural pattern of gases and to identify their role in gas leakage problem, whilst at the same time trying to minimize power consumption. In the proposed device, the temperature detector (DHT 11) the gas detector (MQ2,MQ7 and MQ135) and also humidity sensors are used to determine the environment and the undesirable gas within the manufacturing plant, gauged details can be connected to the web. In addition, our research findings demonstrated substantial energy efficiency and high-precision data analysis relative to conventional protection device strategies. For monitoring the fluctuation of parameters like air pollution levels from their normal levels in this case the sensing devices are connected to the embedded computing system.

Oxidation of aqueous organic molecules in gas-phase pulsed corona discharge affected by sodium dodecyl sulphate: Explanation of variability

Oxidation of waterborne organic compounds by gas-phase pulsed corona discharge (PCD) provides substantial energy efficiency benefits. Surfactant sodium dodecyl sulphate (SDS) alters the energy efficiency of oxidation providing decelerating, neutral or accelerating effect. Determining the causal connection between the pollutant's molecular structure and the effect of SDS addition presents the research objective. Computational chemistry Spartan 14 1.1.4 software was used for modelling of SDS molecule interaction with selected textile dyes and pharmaceuticals with subsequent verification in PCD treatment experiments. Effects of SDS addition were predicted for acid orange 7, indigotetrasulfonate, paracetamol and indomethacin and confirmed experimentally.

Examining green affordable housing policy outcomes in Australia: A systems approach

The Australian affordable rental housing sector has historically faced barriers to green building (GB) adoption due to issues of split-incentives, despite financial support from the commonwealth. This paper explores how a recent shift towards bond-based funding mechanisms offer an opportunity to integrate green building practices, and influence regional social, environmental and economic outcomes. A novel system dynamics model is developed to forecast a business as usual (BAU) and green-building scenario framed around the recently introduced Australian Affordable Housing Bond Aggregator (AHBA) policy framework. The purpose of the model is to examine how a mandate on green building standards together with the use of green versus conventional bonds impact social, environmental and economic outcomes of the framework over a 20-year horizon, within the South East Queensland metropolitan area of Australia. The study determined that the green building framework would deliver 2.37% less housing overall due to higher initial capital costs. However, offers substantial long-term energy and water efficiency benefits, improved affordability for tenants due to reduced utility costs, deferred water and energy infrastructure benefits, and considerable contributions towards Australia’s carbon emission reduction targets. Tenants are expected to benefit from a 45–59% reduction in energy and a 27% decrease in water bills. Moreover, a shift to affordable green building policy could contribute to 2.9% of Australia’s Conference of Parties (2030) carbon emissions reduction target if applied nationally. The study concludes with a sensitivity analysis to reveal policy refinement recommendations that would yield the benefits of green affordable housing without sacrificing the small reduction in housing stock delivered by the proposed program.

A New Core Level Utilization Algorithm for Energy-Efficient Multicore Systems

The energy consumption is becoming a constraint on all computer devices, from smartphones to supercomputers. Consequently, the focus has moved from performance to energy and power consumption. Design metrics are not only based solely on performance, as the energy performance of application executions is becoming the main aspect of architecture. Also, Design metrics depend on, the manufacturers of semiconductor chips which, have implemented multicore processors to boost the level of energy efficiency by using verified techniques for voltage and frequency scaling. To utilize the maximum potential of such architectures, we need to make the right decisions because parameters such as core type, frequency, and utilization typically affect power dissipation and performance. This paper proposes a new algorithm to achieve energy-efficient by monitoring core energy and level utilization control such as: Increasing the number of cores to execute the task, scaling voltage, and frequency. Based on the built model, we analyze the energy efficiency variations for different platform configurations providing the same level of performance. We show that trading the number and type of core with frequency and voltage level and core utilization rate can lead to substantial energy efficiency gains.

PINE: Photonic Integrated Networked Energy efficient datacenters (ENLITENED Program) [Invited

We review the motivation, goals, and achievements of the Photonic Integrated Networked Energy efficient datacenter (PINE) project, which is part of the Advanced Research Projects Agency–Energy (ARPA-E) ENergy-efficient Light-wave Integrated Technology Enabling Networks that Enhance Dataprocessing (ENLITENED) program. The PINE program leverages the unique features of photonic technologies to enable alternative mega-datacenters and high-performance computing (HPC) system architectures that deliver more substantial energy efficiency improvements than can be achieved through link energy efficiency alone. In phase 1 of the program, the PINE system architecture demonstrated an average factor of 2.2 × improvement in transactions/joule across a diverse set of HPC and datacenter applications. In phase 2, PINE will demonstrate an aggressive 1.0 pJ/bit total link budget with high-bandwidth-density dense wavelength-division multiplexing (DWDM) links to enable additional 2.5 × or more efficiency gains through deep resource disaggregation.

Affordable, Energy-Efficient Housing Design for Chile: Achieving Passivhaus Standard with the Chilean State Housing Subsidy

In Chile, it is estimated that the energy demand will continue to increase if substantial energy efficiency measures in housing are not taken. These measures are generally associated with technical and mainly economic difficulties. This paper aims to show the technical and economic feasibility of achieving Passivhaus standard house in Chile, considering the budget of the maximum state subsidy currently available (Chilean Unidad de Fomento (CLF) 2000 ≈ 81,000 USD). The design was simulated in the Passive House Planning Package software to determine if the house could be certified with the selected standard. At the same time, the value of all the items was quantified in order not to exceed the stipulated maximum budget for a house considered as affordable. It was shown that in terms of design it is possible to implement the Passivhaus standard given the current housing subsidy. The designed housing ensures a reduction of 85% in heating demand and a 60% reduction in CO2 emissions during the operation, compared to an average typical Chilean house.

Energy-Efficient Hybrid Precoding Scheme Based on Antenna Selection Technology in Massive Multiple-Input Multiple-Output Systems

Hybrid precoding is a promising technology for massive multiple-input multiple-output (MIMO) systems. It can reduce the number of radio frequency (RF) chains. However, the power consumption is still very high owing to the large-scale antenna array. In this paper, we propose an energy-efficient precoding scheme based on antenna selection technology. The precoding scheme greatly increases the energy efficiency (EE) of the system. In the first step, we derive an exact closed-form expression of EE. Meanwhile, we further study the relationship between the number of transmit antennas and EE on the basis of the exact closed-form expression of EE. We prove that there exists an optimal value. When the number of transmit antennas equals to the value, the EE of the system can reach the maximum by a proper hybrid precoding scheme. Then, we propose an antenna selection algorithm to select antennas from the transmit antennas. And the number of selected antennas equals to the optimal value. Subsequently, we design the analog precoder based on a codebook to maximize the equivalent channel gain. At last, we further improve the EE by baseband digital precoding. The precoding algorithm we proposed offers a compromise between spectral efficiency (SE) and EE in millimeter wave (mmWave) massive MIMO systems. Finally, simulation results validate our theoretical analysis and show that a substantial EE gain can be obtained over the precoding scheme we proposed without large performance loss.

Design and optimization of multi-effect-evaporation-assisted distillation configuration for recovery of 2,3-butanediol from fermentation broth

2,3-butanediol (2,3-BDO) is a precious chemical owing to its extensive industry applications. In addition to the traditional chemical synthesis, the production of 2,3-BDO from biomass-based feedstock is an attractive alternative. Nevertheless, this production way consumes considerable energy because the concentration of product from the conversion of biomass is low. In this study, several novel multi-effect-evaporation-assisted distillation (MEED) configurations are proposed to improve the energy efficiency of 2,3-BDO production from a fermentation broth. The binary interaction parameters between 2,3-BDO and water were determined through regression using experimental data. All configurations were designed and optimized using the sequential quadratic programming methodology. The results indicate that the proposed MEED configurations can create the synergistic effect by combining the multi-effect evaporator and distillation processes, which is able to increase substantial energy efficiency as compared the conventional distillation column. Notably, the total annual cost (TAC) of the MEED configurations with double effect, triple effect, quadruple effect, quintuple effect, and sextuple effect can be reduced by up to 12.3%, 16.9%, 20.1%, 21.7%, and 17.5%, respectively. The proposed MEED configuration with heat integration significantly reduced the TAC by up to 38.9%. Furthermore, CO2 emissions were estimated and compared between a conventional column and the suggested configurations.

Numerical study of a hybrid absorption-compression high temperature heat pump for industrial waste heat recovery

The present paper aims at exploring a hybrid absorption-compression heat pump (HAC-HP) to upgrade and recover the industrial waste heat in the temperature range of 60°C–120°C. The new HAC-HP system proposed has a condenser, an evaporator, and one more solution pump, compared to the conventional HAC-HP system, to allow flexible utilization of energy sources of electricity and waste heat. In the system proposed, the pressure of ammonia-water vapor desorbed in the generator can be elevated by two routes; one is via the compression of compressor while the other is via the condenser, the solution pump, and the evaporator. The results show that more ammonia-water vapor flowing through the compressor leads to a substantial higher energy efficiency due to the higher quality of electricity, however, only a slight change on the system exergy efficiency is noticed. The temperature lift increases with the increasing system recirculation flow ratio, however, the system energy and exergy efficiencies drop towards zero. The suitable operation ranges of HAC-HP are recommended for the waste heat at 60°C, 80°C, 100°C, and 120°C. The recirculation flow ratio should be lower than 9, 6, 5, and 4 respectively for these waste heat, while the temperature lifts are in the range of 9.8°C–27.7 °C, 14.9°C–44.1 °C, 24.4°C–64.1°C, and 40.7°C–85.7°C, respectively, and the system energy efficiency are 0.35–0.93, 0.32–0.90, 0.25–0.85, and 0.14–0.76.

Downlink Massive MIMO Systems: Achievable Sum Rates and Energy Efficiency Perspective for Future 5G Systems

To meet up with the ever increasing subscribers' demand for higher data rates and mobile data traffic growth in the telecommunication industry, the fifth generation (5G) systems is being considered for the next future cellular communication standards. The two principal design requirements being aimed at in 5G are robust data transmission rates in Gigabits and low power consumption systems. Massive multiple input multiple output (M-MIMO) technology is an evolving smart antenna technology which has some key promising potentials to boost 5G networks in meeting the aforementioned requirements. However, there is an emergent concern that increased number of antenna arrays in M-MIMO system could induce high power consumption and poor energy efficiency when deployed at the base stations (BSs). Also, inter-cellular interference which occurs as a result of pilot contamination, fast fading and uncorrelated noise effects in the radio channels are other open issues in M-MIMO system. This work investigates and compare the achievable sum rates and energy efficiency of a downlink single cell M-MIMO systems utilizing linear and nonlinear precoding schemes. First, we have shown how the increasing signal-to-noise ratio and M-antennas impact the achievable sum rates. Furthermore, the energy saving potentials of M-MIMO systems in macro, micro and pico cellular environments when linear and nonlinear precoding schemes are utilized at the BS have been demonstrated. Particularly, by means of power fairness index, the tradeoff among the energy efficiency, sum rate and the system users have also been presented and discussed. Results show that substantial energy efficiency improvements can be achieved in micro and pico cellular environments of downlink M-MIMO systems when non-linear successive interference cancellation precoding is applied compared to linear precoding schemes.

Exploring Capabilities of BIM Tools for Housing Refurbishment in the UK

Currently whole-house refurbishment for substantial energy efficiency improvement of existing housing stock is needed to achieve the targeted 80% CO2 emission reduction. As whole-house refurbishment requires a larger capital investment for lower CO2 emission, the simultaneous use of Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) methodologies are recommended to generate affordable refurbishment solutions. However, two methodologies are difficult to use due to a lack of proper LCC and LCA datasets. As a response to the current problems, many researchers explore potentials in Building Information Modelling (BIM) to improve current construction practice. As a result, a BIM tool - IES IMPACT (Integrated Material Profile And Costing Tool) - has been introduced to the UK construction industry for simultaneous calculation of LCC and LCA. Thus, this research aims at examining the capability and limitation of the IES VE/IMPACT as a BIM tool for whole-house refurbishment. This research reveals that the IES VE/IMPACT is feasible for whole-house refurbishment by providing LCC and LCA information simultaneously for informed decision on refurbishment solution selection. This research shed lights on the current problems lying on the data exchange between two different BIM tools. It is revealed that additional efforts from construction professionals and industry are required to make reliable BIM objects library with LCC and LCA datasets.

Kernel-Based Thread and Data Mapping for Improved Memory Affinity

Reducing the cost of memory accesses, both in terms of performance and energy consumption, is a major challenge in shared-memory architectures. Modern systems have deep and complex memory hierarchies with multiple cache levels and memory controllers, leading to a Non-Uniform Memory Access (NUMA) behavior. In such systems, there are two ways to improve the memory affinity: First, by mapping threads that share data to cores with a shared cache, cache usage and communication performance are optimized. Second, by mapping memory pages to memory controllers that perform the most accesses to them and are not overloaded, the average cost of accesses is reduced. We call these two techniques thread mapping and data mapping, respectively. Thread and data mapping should be performed in an integrated way to achieve a compounding effect that results in higher improvements overall. Previous work in this area requires expensive tracing operations to perform the mapping, or require changes to the hardware or to the parallel application. In this paper, we propose kMAF, a mechanism that performs integrated thread and data mapping in the kernel. kMAF uses the page faults of parallel applications to characterize their memory access behavior and performs the mapping during the execution of the application based on the detected behavior. In an evaluation with a large set of parallel benchmarks executing on three NUMA architectures, kMAF achieved substantial performance and energy efficiency improvements, close to an Oracle-based mechanism and significantly higher than previous proposals.