Huddling in groups leads to daily energy savings in free-living African Four-Striped Grass Mice, Rhabdomys pumilio

1. Free-living animals make complex decisions associated with optimizing energy and nutrient intake. In environments where ambient temperatures fall below the thermoneutral zone, homeotherms must choose whether or not to forage, how long and what to forage for, and whether or not to perform activities that conserve energy.

Shedding Light on the light bulb puzzle: the role of attitudes and perceptions in the adoption of energy efficient light bulbs

Despite the potential energy savings and economic benefits associated with compact fluorescent light bulbs, their adoption by the residential sector has been limited to date. In this paper, we present a theoretical model that focuses on the agents' ability to perceive the correct cost of lighting and on the role of environmental attitudes as key determinants of the adoption decision. We use original data from Ireland to test our theoretical predictions. Our results emphasize the importance of education, information and environmental awareness in the adoption decision.

Cities Ready for Energy Crises - Building Urban energy Resilience

Various sources indicate that threats to modern cities lie in the availability of essential streams, among which energy. Most cities are strongly reliant on fossil fuels; not one case of a fully self-sufficient city is known. Engineering resilience is the rate at which a system returns to a single steady or cyclic state following a perturbation. Certain resilience, for the duration of a crisis, would improve the urban capability to survive such a period without drastic measures.
The capability of cities to prepare for and respond to energy crises in the near future is supported by greater or temporary self-sufficiency. The objective of the underlying research is a model for a city – including its surrounding rural area – that can sustain energy crises. Therefore, accurate monitoring of the current urban metabolism is needed for the use of energy. This can be used to pinpoint problem areas. Furthermore, a sustainable energy system is needed, in which the cycle is better closed. This will require a three-stepped approach of energy savings, energy exchange and sustainable energy generation. Essential is the capacity to store energy surpluses for periods of shortage (crises).
The paper discusses the need for resilient cities and the approach to make cities resilient to energy crises.

Strategies for Energy-Efficient Resource Management of Hybrid Programming Models

Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

On the potential of significance-driven execution for energy-aware HPC

Dynamic Voltage and Frequency Scaling (DVFS) exhibits fundamental limitations as a method to reduce energy consumption in computing systems. In the HPC domain, where performance is of highest priority and codes are heavily optimized to minimize idle time, DVFS has limited opportunity to achieve substantial energy savings. This paper explores if operating processors Near the transistor Threshold Volt- age (NTV) is a better alternative to DVFS for break- ing the power wall in HPC. NTV presents challenges, since it compromises both performance and reliability to reduce power consumption. We present a first of its kind study of a significance-driven execution paradigm that selectively uses NTV and algorithmic error tolerance to reduce energy consumption in performance- constrained HPC environments. Using an iterative algorithm as a use case, we present an adaptive execution scheme that switches between near-threshold execution on many cores and above-threshold execution on one core, as the computational significance of iterations in the algorithm evolves over time. Using this scheme on state-of-the-art hardware, we demonstrate energy savings ranging between 35% to 67%, while compromising neither correctness nor performance.

Energy Efficiency through Significance-Based Computing

An extension of approximate computing, significance-based computing exploits applications' inherent error resiliency and offers a new structural paradigm that strategically relaxes full computational precision to provide significant energy savings with minimal performance degradation.

HERQULES:System level cross-layer design exploration for efficient energy-quality trade-offs

In this paper, we present a unique cross-layer design framework that allows systematic exploration of the energy-delay-quality trade-offs at the algorithm, architecture and circuit level of design abstraction for each block of a system. In addition, taking into consideration the interactions between different sub-blocks of a system, it identifies the design solutions that can ensure the least energy at the "right amount of quality" for each sub-block/system under user quality/delay constraints. This is achieved by deriving sensitivity based design criteria, the balancing of which form the quantitative relations that can be used early in the system design process to evaluate the energy efficiency of various design options. The proposed framework when applied to the exploration of energy-quality design space of the main blocks of a digital camera and a wireless receiver, achieves 58% and 33% energy savings under 41% and 20% error increase, respectively. © 2010 ACM.

VEDA:Variation-aware energy-efficient discrete Wavelet Transform architecture

In this paper, we present a unified approach to an energy-efficient variation-tolerant design of Discrete Wavelet Transform (DWT) in the context of image processing applications. It is to be noted that it is not necessary to produce exactly correct numerical outputs in most image processing applications. We exploit this important feature and propose a design methodology for DWT which shows energy quality tradeoffs at each level of design hierarchy starting from the algorithm level down to the architecture and circuit levels by taking advantage of the limited perceptual ability of the Human Visual System. A unique feature of this design methodology is that it guarantees robustness under process variability and facilitates aggressive voltage over-scaling. Simulation results show significant energy savings (74% - 83%) with minor degradations in output image quality and avert catastrophic failures under process variations compared to a conventional design. © 2010 IEEE.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Application-Level Energy Awareness for OpenMP

Power, and consequently energy, has recently attained first-class system resource status, on par with conventional metrics such as CPU time. To reduce energy consumption, many hardware- and OS-level solutions have been investigated. However, application-level information - which can provide the system with valuable insights unattainable otherwise - was only considered in a handful of cases. We introduce OpenMPE, an extension to OpenMP designed for power management. OpenMP is the de-facto standard for programming parallel shared memory systems, but does not yet provide any support for power control. Our extension exposes (i) per-region multi-objective optimization hints and (ii) application-level adaptation parameters, in order to create energy-saving opportunities for the whole system stack. We have implemented OpenMPE support in a compiler and runtime system, and empirically evaluated its performance on two architectures, mobile and desktop. Our results demonstrate the effectiveness of OpenMPE with geometric mean energy savings across 9 use cases of 15 % while maintaining full quality of service.

Energy and environmental forensic analysis for public buildings.

This paper outlines a forensic method for analysing the energy, environmental and comfort performance of a building. The method has been applied to a recently developed event space in an Irish public building, which was evaluated using on-site field studies, data analysis, building simulation and occupant surveying. The method allows for consideration of both the technological and anthropological aspects of the building in use and for the identification of unsustainable operational practice and emerging problems. The forensic analysis identified energy savings of up to 50%, enabling a more sustainable, lower-energy operational future for the building. The building forensic analysis method presented in this paper is now planned for use in other public and commercial buildings.

Achieving Energy Saving through Proxying Applications on behalf of Idle Devices

Several studies in the past have revealed that network end user devices are left powered up 24/7 even when idle just for the sake of maintaining Internet connectivity. Network devices normally support low power states but are kept inactive due to their inability to maintain network connectivity. The Network Connectivity Proxy (NCP) has recently been proposed as an effective mechanism to impersonate network connectivity on behalf of high power devices and enable them to sleep when idle without losing network presence. The NCP can efficiently proxy basic networking protocol, however, proxying of Internet based applications have no absolute solution due to dynamic and non-predictable nature of the packets they are sending and receiving periodically. This paper proposes an approach for proxying Internet based applications and presents the basic software architectures and capabilities. Further, this paper also practically evaluates the proposed framework and analyzes expected energy savings achievable under-different realistic conditions.

The energetics of huddling in two species of mole-rat (Rodentia: Bathyergidae)

Small rodents with a large surf ace-area-to-volume ratio and a high thermal conductance are likely to experience conditions where they have to expend large: amounts of energy in order to maintain a constant body temperature at low ambient temperatures. The survival of small rodents is thus dependent on their ability to reduce heat loss and increase heat production at low ambient temperatures. Two such animals are the social subterranean rodents Cryptomys damarensis (the Damaraland mole-rat) and Cryptomys hottentotus natalensis (the Natal mole-rat). This study examined the energy savings associated with huddling as a behavioural thermoregulatory mechanism to conserve energy in both these species. Individual oxygen consumption (VO2) was measured in groups ranging in size from one to 15 huddling animals for both species at ambient temperatures of 14, 18, 22, 26 and 30 degrees C. Savings in energy (VO2) were then compared between the two species. Significant differences in VO2 (p

Intelligent demand response electric water heating to integrate wind power in Ireland

Dwindling fossil fuel resources and pressures to reduce greenhouse gas (GHG) 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 that supply instantaneously meets demand and that robust operating standards are maintained to ensure a consistent supply of high quality electricity to end-users. 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 (DSM) with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating (EWH) has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper, a continuous Direct Load Control (DLC) EWH algorithm is applied in a liberalized market environment using actual historical electricity system and market data to examine the potential energy savings, cost reductions and electricity system operational improvements.