Dynamic remapping decisions in multi-phase parallel computations

The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary

An optimal repartitioning decision policy

A central problem to parallel processing is the determination of an effective partitioning of workload to processors. The effectiveness of any given partition is dependent on the stochastic nature of the workload. The problem of determining when and if the stochastic behavior of the workload has changed enough to warrant the calculation of a new partition is treated. The problem is modeled as a Markov decision process, and an optimal decision policy is derived. Quantification of this policy is usually intractable. A heuristic policy which performs nearly optimally is investigated empirically. The results suggest that the detection of change is the predominant issue in this problem

Lower levels of damaged protein biomarkers in the plasma of overweight type 2 diabetic men following supplementation with a standardised bilberry extract

Peer reviewedPublisher PD

Proteomics reveals that a high-fat diet induces rapid changes in hypothalamic proteins related to neuronal damage and inflammation

Peer reviewedPublisher PD

Development of an adaptive window-opening algorithm to predict the thermal comfort, energy use and overheating in buildings

This investigation of the window opening data from extensive field surveys in UK office buildings demonstrates: 1) how people control the indoor environment by opening windows; 2) the cooling potential of opening windows; and 3) the use of an ‘adaptive algorithm’ for predicting window opening behaviour for thermal simulation in ESP-r. It was found that when the window was open the mean indoor and outdoor temperatures were higher than when closed, but show that nonetheless there was a useful cooling effect from opening a window. The adaptive algorithm for window opening behaviour was then used in thermal simulation studies for some typical office designs. The thermal simulation results were in general agreement with the findings of the field surveys. The adaptive algorithm is shown to provide insights not available using non adaptive simulation methods and can assist in achieving more comfortable, lower energy buildings while avoiding overheating

Considering the impact of situation-specific motivations and constraints in the design of naturally ventilated and hybrid buildings

A simple logical model of the interaction between a building and its occupants is presented based on the principle that if free to do so, people will adjust their posture, clothing or available building controls (windows, blinds, doors, fans, and thermostats) with the aim of achieving or restoring comfort and reducing discomfort. These adjustments are related to building design in two ways: first the freedom to adjust depends on the availability and ease-of-use of control options; second the use of controls affects building comfort and energy performance. Hence it is essential that these interactions are considered in the design process. The model captures occupant use of controls in response to thermal stimuli (too warm, too cold etc.) and non-thermal stimuli (e.g. desire for fresh air). The situation-specific motivations and constraints on control use are represented through trigger temperatures at which control actions occur, motivations are included as negative constraints and incorporated into a single constraint value describing the specifics of each situation. The values of constraints are quantified for a range of existing buildings in Europe and Pakistan. The integration of the model within a design flow is proposed and the impact of different levels of constraints demonstrated. It is proposed that to minimise energy use and maximise comfort in naturally ventilated and hybrid buildings the designer should take the following steps: 1. Provide unconstrained low energy adaptive control options where possible, 2. Avoid problems with indoor air quality which provide motivations for excessive ventilation rates, 3. Incorporate situation-specific adaptive behaviour of occupants in design simulations, 4. Analyse the robustness of designs against variations in patterns of use and climate, and 5. Incorporate appropriate comfort standards into the operational building controls (e.g. BEMS)

Comfort driven adaptive window opening behaviour and the influence of building design

It is important to understand and model the behaviour of occupants in buildings and how this behaviour impacts energy use and comfort. It is similarly important to understand how a buildings design affects occupant comfort, occupant behaviour and ultimately the energy used in the operation of the building. In this work a behavioural algorithm for window opening developed from field survey data has been implemented in a dynamic simulation tool. The algorithm is in alignment with the proposed CEN standard for adaptive thermal comfort. The algorithm is first compared to the field study data then used to illustrate the impact of adaptive behaviour on summer indoor temperatures and heating energy. The simulation model is also used to illustrate the sensitivity of the occupant adaptive behaviour to building design parameters such as solar shading and thermal mass and the resulting impact on energy use and comfort. The results are compared to those from other approaches to model window opening behaviour. The adaptive algorithm is shown to provide insights not available using non adaptive simulation methods and can assist in achieving more comfortable and lower energy buildings

Theory of the critical current in two-band superconductors with application to MgB2

Using a Green's function formulation of the superfluid current j_s, where a momentum q_s is applied to the Cooper pair, we have calculated j_s as a function of q_s, temperature, and impurity scattering for a two-band superconductor. We consider both renormalized BCS and full strong-coupling Eliashberg theory. There are two peaks in the current as a function of q_s due to the two energy scales for the gaps and this can give rise to non-standard behavior for the critical current. The critical current j_c, which is given as the maximum in j_s, can exhibit a kink as a function of temperature as the maximum is transferred from one peak to other. Other temperature variations are also possible and the universal BCS behavior is violated. The details depend on the material parameters of the system, such as the amount of coupling between the bands, the gap anisotropy, the Fermi velocities, and the density of states of each band. The Ginzburg-Landau relation between j_c, the penetration depth lambda_L and thermodynamic critical field H_c, is modified. Using Eliashberg theory with the electron-phonon spectral densities given from bandstructure calculations, we have applied our calculations for j_s and j_c to the case of MgB2 and find agreement with experiment.Comment: 13 pages, 7 figures, submitted to PR