Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

Improving the ultra-low-power performance of IEEE 802.15.6 by adaptive synchronisation

In ultra-low data rate wireless sensor networks (WSNs) waking up just to listen to a beacon every superframe can be a major waste of energy. This study introduces MedMAC, a medium access protocol for ultra-low data rate WSNs that achieves significant energy efficiency through a novel synchronisation mechanism. The new draft IEEE 802.15.6 standard for body area networks includes a sub-class of applications such as medical implantable devices and long-term micro miniature sensors with ultra-low power requirements. It will be desirable for these devices to have 10 years or more of operation between battery changes, or to have average current requirements matched to energy harvesting technology. Simulation results are presented to show that the MedMAC allows nodes to maintain synchronisation to the network while sleeping through many beacons with a significant increase in energy efficiency during periods of particularly low data transfer. Results from a comparative analysis of MedMAC and IEEE 802.15.6 MAC show that MedMAC has superior efficiency with energy savings of between 25 and 87 for the presented scenarios. © 2011 The Institution of Engineering and Technology.

Integrating wind power using intelligent electric water heating

Dwindling fossil fuel resources and pressures to reduce greenhouse gas emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is to instantaneously meet demand, to operate to standards and reduce greenhouse gas emissions. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating has been studied previously, particularly at the domestic level to provide load control, peak shave and to bene?t end-users ?nancially with lower bills, particularly in vertically integrated monopolies. In this paper a number of continuous direct load control demand response based electric water heating algorithms are modelled to test the effectiveness of wholesale electricity market signals to study the system bene?ts. The results are compared and contrasted to determine which control algorithm showed the best potential for energy savings, system marginal price savings and wind integration.

Retrofit versus new-build house using life-cycle assessment

This paper reports the findings of research on the environmental performance of two case-study houses, a retrofit and new build. The retrofit was completed to a Passivhaus standard while the new build was completed to current Irish building regulations. Environmental performance of the retrofit and new build was measured using life-cycle assessments, examining the assembly, operational and end-of-life stage over life spans of 50 and 80 years. Using primary information, life-cycle assessment software and life-cycle assessment databases the environmental impacts of each stage were modelled. The operational stage of both case studies was found to be the source of the most significant environmental damage, followed by the assembly and the end-of-life stage respectively. The relative importance of the assembly and end-of-life stage decreased as the life span increased. It was found that the retrofit house studied outperformed the new build in the assembly and operational stage, whereas the new build performed better in the end-of-life stage; however, this is highly sensitive, depending on the standards to which both are completed. Operational energy savings pre- and post-retrofit were significant, indicating the future potential for adoption of high-quality retrofitting practices.

RFID based Efficient Lighting Control

The Kyoto Protocol and the European Energy Performance of Buildings Directive put an onus on governments
and organisations to lower carbon footprint in order to contribute towards reducing global warming. A key
parameter to be considered in buildings towards energy and cost savings is its indoor lighting that has a major
impact on overall energy usage and Carbon Dioxide emissions. Lighting control in buildings using Passive
Infrared sensors is a reliable and well established approach; however, the use of only Passive Infrared does not
offer much savings towards reducing carbon, energy, and cost. Accurate occupancy monitoring information can
greatly affect a building’s lighting control strategy towards a greener usage. This paper presents an approach for
data fusion of Passive Infrared sensors and passive Radio Frequency Identification (RFID) based occupancy
monitoring. The idea is to have efficient, need-based, and reliable control of lighting towards a green indoor
environment, all while considering visual comfort of occupants. The proposed approach provides an estimated
13% electrical energy savings in one open-plan office of a University building in one working day. Practical
implementation of RFID gateways provide real-world occupancy profiling data to be fused with Passive
Infrared sensing towards analysis and improvement of building lighting usage and control.

Gas Hydrate Inhibition: A Review of the Role of Ionic Liquids

Ionic liquids (ILs) are popular designer green chemicals with great potential for use in diverse energy-related applications. Apart from the well-known low vapor pressure, the physical properties of ILs, such as hydrogen-bond-forming capacity, physical state, shape, and size, can be fine-tuned for specific applications. Natural gas hydrates are easily formed in gas pipelines and pose potential problems to the oil and natural gas industry, particularly during deep-sea exploration and production. This review summarizes the recent advances in IL research as dual-function gas hydrate inhibitors. Almost all of the available thermodynamic and kinetic inhibition data in the presence of ILs have been systematically reviewed to evaluate the efficiency of ILs in gas hydrate inhibition, compared to other conventional thermodynamic and kinetic gas hydrate inhibitors. The principles of natural gas hydrate formation, types of gas hydrates and their inhibitors, apparatuses and methods used, reported experimental data, and theoretical methods are thoroughly and critically discussed. The studies in this field will facilitate the design of advanced ILs for energy savings through the development of efficient low-dosage gas hydrate inhibitors.

Heterogeneous error-resilient scheme for spectral analysis in ultra-low power wearable electrocardiogram devices

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.

Overview on bio-based building material made with plant aggregate

Global warming, energy savings, and life cycle analysis issues are factors that have contributed to the rapid expansion of plant-based materials for buildings, which can be qualified as environmental-friendly, sustainable and efficient multifunctional materials. This review presents an overview on the several possibilities developed worldwide about the use of plant aggregate to design bio-based building materials. The use of crushed vegetal aggregates such as hemp (shiv), flax, coconut shells and other plants associated to mineral binder represents the most popular solution adopted in the beginning of this revolution in building materials. Vegetal aggregates are generally highly porous with a low apparent density and a complex architecture marked by a multi-scale porosity. These geometrical characteristics result in a high capacity to absorb sounds and have hygro-thermal transfer ability. This is one of the essential characteristics which differ of vegetal concrete compared to the tradition mineral-based concretes. In addition, the high flexibility of the aggregates leads to a non-fragile elasto-plastic behavior and a high deformability under stress, lack of fracturing and marked ductility with absorbance of the strains ever after having reached the maximum mechanical strength. Due to the sensitivity to moisture, the assessment of the durability of vegetal concrete constitutes one of the next scientific challenging of bio-based building materials.

Energy efficiency investments in the home: Swiss homeowners and expectations about future energy prices

Using conjoint choice experiments, we surveyed 473 Swiss homeowners about their preferences for energy efficiency home renovations.We find that homeowners are responsive to the upfront costs of the renovation projects, governmentoffered rebates, savings in energy expenses, time horizon over which such savings would be realized, and thermal comfort improvement. The implicit discount rate is low, ranging from 1.5 to 3%, depending on model specification. This is consistent with Hassett and Metcalf (1993) and Metcalf and Rosenthal (1995), and with the fact that our scenarios contain no uncertainty. Respondents who feel completely uncertain about future energy prices are more likely to select the status quo (no renovations) in any given choice task and weight the costs of the investments more heavily than the financial gains (subsidies and savings on the energy bills). Renovations are more likely when respondents believe that climate change considerations are important determinants of home renovations. Copyright © 2013 by the IAEE. All rights reserved.

Life-Cycle Energy Analysis of a Modular/Off-Site Building School

This paper is concerned with assessing the building’s the energy efficiency and qualities of a modular design for the education industry, in order assess the long economic benefits. The research includes a life-cycle energy and cost analysis of the school building design, predicting the impact on the operational cost of the building as a result of the addition of photovoltaic panels. The paper also includes a comparative study between the ECO Modular Solutions building, and a current standard prefabricated school building, quantifying the savings in CO2 emissions and savings in cost.

Whole-Vehicle modelling of exhaust energy recovery on a diesel-electric hybrid bus

Hybrid vehicles can use energy storage systems to disconnect the engine from the driving wheels of the vehicle. This enables the engine to be run closer to its optimum operating condition, but fuel energy is still wasted through the exhaust system as heat. The use of a turbogenerator on the exhaust line addresses this problem by capturing some of the otherwise wasted heat and converting it into useful electrical energy.

This paper outlines the work undertaken to model the engine of a diesel-electric hybrid bus, coupled with a hybrid powertrain model which analysed the performance of a hybrid vehicle over a drive-cycle. The distribution of the turbogenerator power was analysed along with the effect on the fuel consumption of the bus. This showed that including the turbogenerator produced a 2.4% reduction in fuel consumption over a typical drive-cycle.

The hybrid bus generator was then optimised to improve the performance of the combined vehicle/engine package and the turbogenerator was then shown to offer a 3.0% reduction in fuel consumption. The financial benefits of using the turbogenerator were also considered in terms of fuel savings for operators. For an average bus, a turbogenerator could reduce fuel costs by around £1200 per year.

Energy versus data integrity trade-offs in embedded high-density logic compatible dynamic memories

Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.