HAPPE: Human and Application-Driven Frequency Scaling for Processor Power Efficiency

Abstract-Conventional dynamic voltage and frequency scaling techniques use high CPU utilization as a predictor for user dissatisfaction, to which they react by increasing CPU frequency. In this paper, we demonstrate that for many interactive applications, perceived performance is highly dependent upon the particular user and application, and is not linearly related to CPU utilization. This observation reveals an opportunity for reducing power consumption. We propose Human and Application driven frequency scaling for Processor Power Efficiency (HAPPE), an adaptive user-and-application-aware dynamic CPU frequency scaling technique. HAPPE continuously adapts processor frequency and voltage to the learned performance requirement of the current user and application. Adaptation to user requirements is quick and requires minimal effort from the user (typically a handful of key strokes). Once the system has adapted to the user's performance requirements, the user is not required to provide continued feedback but is permitted to provide additional feedback to adjust the control policy to changes in preferences. HAPPE was implemented on a Linux-based laptop and evaluated in 22 hours of controlled user studies. Compared to the default Linux CPU frequency controller, HAPPE reduces the measured system-wide power consumption of CPU-intensive interactive applications by 25 percent on average while maintaining user satisfaction. Index Terms-Power, CPU frequency scaling, user-driven study, mobile systems Ç 1I NTRODUCTION P OWER efficiency has been a major technology driver for battery-powered mobile systems, such as mobile phones, personal digital assistants, MP3 players, and laptops. Power efficiency has also become a new focus for line-powered desktop systems and data centers because of its impact on power dissipation and chip temperature, which affect performance, reliability, and lifetime. Processor power consumption is often a substantial portion of system power consumption in mobile systems Traditional CPU power management approaches can lose sight of an important fact: The ultimate goal of any computer system is to satisfy its users, not to execute a particular number of instructions per second. Although CPU utilization is a good indication of processor performance, the actual perceivable system performance depends on individual users and applications, and user satisfaction is not linearly related to CPU utilization. We conducted a study on 10 users with four interactive applications and found that for some applications, some users are satisfied with system performance when the processor is at the lowest frequency, while other users may not be satisfied even when it operates at the highest frequency. We also found that users may be insensitive to varying processor frequency for one application, but may be very sensitive to such changes for another application. Traditional DVFS policies that consider only CPU utilization or other useroblivious performance metrics are often too pessimistic about user performance requirements, and use a high frequency to satisfy all users, resulting in wasted power. Similar findings were also reported in other studies In this paper, we propose Human and Application driven frequency scaling for Processor Power Efficiency (HAPPE), a CPU DVFS technique that adapts voltage and frequency to the performance requirement of the curren

The aerodynamic characteristics of an exposed racing car wheel

The aerodynamics of an exposed racing car wheel have been analysed using experimental and computational (CFD) techniques. A 40% full-scale pneumatic tyre/wheel assembly was used for the experimental investigations and the exact geometry was replicated in the CFD model. The wheel had an aspect ratio of 0.53 and the tests were conducted at a Reynolds number, based on the wheel diameter, of 2.5 x 10 . Both rotating and stationary wheels were tested with moving and fixed ground-planes, respectively. The experiments were conducted using new and existing methods of data acquisition and analysis. A non-intrusive radio telemetry system was successfully designed and developed that enabled surface static pressure data to be transmitted from a rotating wheel to a local PC. Other experimental techniques included the use of particle image velocimetry (PIV) and a pneumatic non-embedded five-hole pressure probe to investigate the flow-field about the wheel. The early flow separation, which is a characteristic of the rotating wheel, was observed in the surface static pressure distributions and PIV velocity fields. Lift and drag forces were found to decrease as a result of wheel rotation, which agreed with the work of other investigators, and the mechanisms responsible for such force reductions are postulated. The wake structures were investigated and showed weaker streamwise vorticity for the rotating wheel compared to the stationary wheel. The most important and remarkable aspect of this work was the experimental observation and subsequent CFD prediction of the rear jetting flow mechanism whose existence was previously theoretically predicted by another investigator. The PIV velocity fields clearly show the rear jetting phenomenon and this is further corroborated by a negative pressure peak in the surface pressure distributions on the wheel centreline. The effects the rear jetting phenomenon has on the wake mechanics, and hence the forces acting on the rotating wheel, are postulated

A Comparative Evaluation of Latency-Aware Energy Optimization Approaches in Many-Core Systems (Invited Paper)

Many applications vary a lot in execution time depending on their workload. A prominent example is image processing applications, where the execution time is dependent on the content or the size of the processed input images. An interesting case is when these applications have quality-of-service requirements such as soft deadlines, that they should meet as good as possible. A further complicated case is when such applications have one or even multiple further objectives to optimize like, e.g., energy consumption. Approaches that dynamically adapt the processing resources to application needs under multiple optimization goals and constraints can be characterized into the application-specific and feedback-based techniques. Whereas application-specific approaches typically statically use an offline stage to determine the best configuration for each known workload, feedback-based approaches, using, e.g., control theory, adapt the system without the need of knowing the effect of workload on these goals. In this paper, we evaluate a state-of-the-art approach of each of the two categories and compare them for image processing applications in terms of energy consumption and number of deadline misses on a given many-core architecture. In addition, we propose a second feedback-based approach that is based on finite state machines (FSMs). The obtained results suggest that whereas the state-of-the-art application-specific approach is able to meet a specified latency deadline whenever possible while consuming the least amount of energy, it requires a perfect characterization of the workload on a given many-core system. If such knowledge is not available, the feedback-based approaches have their strengths in achieving comparable energy savings, but missing deadlines more often

High-powered electric motorcycle integrated performance studies

Electric vehicles and low carbon technology are currently at the forefront of research due to the need to rapidly reduce global carbon emissions. Significant effort has been invested into the improvement of electric cars but comparatively little for electric motorcycles, especially high-performance electric motorcycles. To achieve high-performance it is important to capture relevant design trade-offs and plan for vehicle optimisation prior to starting detailed design. These design trade-offs typically involve optimal sizing of the vehicle battery, electric motor, and motor drive, as well as the determination of the optimum lift-to-drag ratio. A full vehicle analysis including pertinent mechanical and electrical elements is required to perform this properly, as the system is highly interdependent. Existing models are shown to be lacking in key areas, notably the integration of an appropriate battery model, a realistic electric motor model (reflecting modern high-performance electric motorcycle design practices), and an appropriate tyre model, amongst other issues. The work in this thesis builds and validates a full vehicle model of a modern high-performance electric motorcycle. This is accomplished by first developing a rigid body dynamics motorcycle model that includes a full tyre model, the effects of downforce, differing front and rear tyres, and front-wheel drive. Further work is then undertaken to increase the depth and suitability of the electric powertrain modelling for high-performance electric motorcycles. Here, the battery thermal and electrical responses are modelled as well as the powertrain torque response, including saturation and loss modelling of the motor, motor drive and final drive. To validate these models both motor dynamometer testing and battery cycle testing is performed. An accelerated battery testing procedure is also developed to reduce the time required to properly evaluate and characterise test cells for performance evaluation. Having developed the vehicle model, a lap simulation procedure is then developed, implemented, and validated. Validation uses lap data acquired at multiple events including the Isle of Man TT Zero, Pikes Peak International Hillclimb (PPHIC) and Elvington Airfield Land speed record attempts. The lap simulation is then extended to include the effects of energy deployment strategy on lap time. This includes a different methodology for designs that are limited by the battery thermal performance and those that are not. This deployment strategy implementation is shown to significantly affect lap time. The work continues with lap time simulations of the Isle of Man TT Zero and PPHIC, investigating the respective influence of energy management on battery sizing. This shows that it is important to include the energy management strategy into the design evaluation and that the energy management trade-offs are specific to each race event. Additionally, analysis shows that situations, where battery temperature management strategies dominate energy management strategies, should be avoided by the proper design of a battery cooling system. This is because the penalty associated with reducing battery temperature through power and velocity limitations is higher than that of including sufficient cooling. The lap time sensitivity to mass, motor inertia, winglet lift-to-drag ratios and other design variables are explored with recommendations made for the Isle of Man TT Zero race and PPHIC. It is shown that by properly including representations of the underlying physics using a holistic modelling approach, and utilising a quantifiable objective, the relative contribution of individual elements can be quantified and directly compared. The significance of this from a full vehicle design standpoint is large as now vehicle development can be accurately targeted into areas that provide significant benefit. This can greatly improve the efficiency of the development process and the ultimate performance of the motorcycle

Inverse Dynamics Problems

The inverse dynamics problem was developed in order to provide researchers with the state of the art in inverse problems for dynamic and vibrational systems. Contrasted with a forward problem, which solves for the system output in a straightforward manner, an inverse problem searches for the system input through a procedure contaminated with errors and uncertainties. An inverse problem, with a focus on structural dynamics, determines the changes made to the system and estimates the inputs, including forces and moments, to the system, utilizing measurements of structural vibration responses only. With its complex mathematical structure and need for more reliable input estimations, the inverse problem is still a fundamental subject of research among mathematicians and engineering scientists. This book contains 11 articles that touch upon various aspects of inverse dynamic problems

Optimisation of racing car suspensions featuring inerters

Racing car suspensions are a critical system in the overall performance of the vehicle. They must be able to accurately control ride dynamics as well as influencing the handling characteristics of the vehicle and providing stability under the action of external forces. This work is a research study on the design and optimisation of high performance vehicle suspensions using inerters. The starting point is a theoretical investigation of the dynamics of a system fitted with an ideal inerter. This sets the foundation for developing a more complex and novel vehicle suspension model incorporating real inerters. The accuracy and predictability of this model has been assessed and validated against experimental data from 4- post rig testing. In order to maximise overall vehicle performance, a race car suspension must meet a large number of conflicting objectives. Hence, suspension design and optimisation is a complex task where a compromised solution among a set of objectives needs to be adopted. The first task in this process is to define a set of performance based objective functions. The approach taken was to relate the ride dynamic behaviour of the suspension to the overall performance of the race car. The second task of the optimisation process is to develop an efficient and robust optimisation methodology. To address this, a multi-stage optimisation algorithm has been developed. The algorithm is based on two stages, a hybrid surrogate model based multiobjective evolutionary algorithm to obtain a set of non-dominated optimal suspension solutions and a transient lap-time simulation tool to incorporate external factors to the decision process and provide a final optimal solution. A transient lap-time simulation tool has been developed. The minimum time manoeuvring problem has been defined as an Optimal Control problem. A novel solution method based on a multi-level algorithm and a closed-loop driver steering control has been proposed to find the optimal lap time. The results obtained suggest that performance gains can be obtained by incorporating inerters into the suspension system. The work suggests that the use of inerters provides the car with an optimised aerodynamic platform and the overall stability of the vehicle is improved

Artificial neural networks for vibration based inverse parametric identifications: A review

Vibration behavior of any solid structure reveals certain dynamic characteristics and property parameters of that structure. Inverse problems dealing with vibration response utilize the response signals to find out input factors and/or certain structural properties. Due to certain drawbacks of traditional solutions to inverse problems, ANNs have gained a major popularity in this field. This paper reviews some earlier researches where ANNs were applied to solve different vibration-based inverse parametric identification problems. The adoption of different ANN algorithms, input-output schemes and required signal processing were denoted in considerable detail. In addition, a number of issues have been reported, including the factors that affect ANNs’ prediction, as well as the advantage and disadvantage of ANN approaches with respect to general inverse methods Based on the critical analysis, suggestions to potential researchers have also been provided for future scopes

A system for aiding the user assimilation of acquired motorsport data

A racing car is a complex machine, featuring many adjustable components, used to influence the car's performance and tune it to a circuit, the prevailing conditions and the driver's style. A race team must continually monitor the car's performance and a race engineer communicates with the driver to decide how best to optimise the car as well as how to extract most from the driver himself. Analysis of acquired vehicle performance data is an intrinsic part of this process. This thesis presents an investigation into methods to aid the motorsport user's assimilation of acquired vehicle performance data. The work was directly prompted by personal experience and published opinion. These both find that the full potential of acquired data in motorsport is seldom realised, primarily because of the time available to analyse data with the resources available to a racing team. A complete solution including data management methods and visualisation tools was conceived here as a means of addressing these issues. This work focuses on part of the overall solution concept; the development of a visualisation application giving the user a detailed and realistic three-dimensional replay of a data set. The vehicle s motion is recreated from acquired data through a kinematic vehicle model driven by measured damper and ride height data. Ground displacement is computed from wheel speed and accelerometer measurements as well as a new optical sensor approach aiming to achieve better accuracy. This implements a two dimensional auto-correlation of doubly exposed ground images, calibrated to distance on the basis of an integrated ride height measurement. Three sensor units are used to allow not only displacement but also heading data to be derived. The result of the work described in this thesis is the proof of principle of both a display and sensor system, both of which were deemed worthy of further study and development to fully meet the demands of the motorsport application. The visualisation tool presented a new and applicable method of viewing acquired data, whilst the sensor was proven as a new method of deriving vehicle position data, from potentially low cost hardware.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Model-Based Control Techniques for Automotive Applications

Two different topics are covered in the thesis. Model Predictive Control applied to the Motion Cueing Problem In the last years the interest about dynamic driving simulators is increasing and new commercial solutions are arising. Driving simulators play an important role in the development of new vehicles and advanced driver assistance devices: in fact, on the one hand, having a human driver on a driving simulator allows automotive manufacturers to bridge the gap between virtual prototyping and on-road testing during the vehicle development phase; on the other hand, novel driver assistance systems (such as advanced accident avoidance systems) can be safely tested by having the driver operating the vehicle in a virtual, highly realistic environment, while being exposed to hazardous situations. In both applications, it is crucial to faithfully reproduce in the simulator the driver's perception of forces acting on the vehicle and its acceleration. This has to be achieved while keeping the platform within its limited operation space. Such strategies go under the name of Motion Cueing Algorithms. In this work, a particular implementation of a Motion Cueing algorithm is described, that is based on Model Predictive Control technique. A distinctive feature of such approach is that it exploits a detailed model of the human vestibular system, and consequently differs from standard Motion Cueing strategies based on Washout Filters: such feature allows for better implementation of tilt coordination and more efficient handling of the platform limits. The algorithm has been evaluated in practice on a small-size, innovative platform, by performing tests with professional drivers. Results show that the MPC-based motion cueing algorithm allows to effectively handle the platform working area, to limit the presence of those platform movements that are typically associated with driver motion sickness, and to devise simple and intuitive tuning procedures. Moreover, the availability of an effective virtual driver allows the development of effective predictive strategies, and first simulation results are reported in the thesis. Control Techniques for a Hybrid Sport Motorcycle Reduction of the environmental impact of transportation systems is a world wide priority. Hybrid propulsion vehicles have proved to have a strong potential to this regard, and different four-wheels solutions have spread out in the market. Differently from cars, and even if they are considered the ideal solution for urban mobility, motorbikes and mopeds have not seen a wide application of hybrid propulsion yet, mostly due to the more strict constraints on available space and driving feeling. In the thesis, the problem of providing a commercial 125cc motorbike with a hybrid propulsion system is considered, by adding an electric engine to its standard internal combustion engine. The aim for the prototype is to use the electrical machine (directly keyed on the drive shaft) to obtain a torque boost during accelerations, improving and regularizing the supplied power while reducing the emissions. Two different control algorithms are proposed 1) the first is based on a standard heuristic with adaptive features, simpler to implement on the ECU for the prototype; 2) the second is a torque-split optimal-control strategy, managing the different contributions from the two engines. A crucial point is the implementation of a Simulink virtual environment, realized starting from a commercial tool, VI-BikeRealTime, to test the algorithms. The hybrid engine model has been implemented in the tool from scratch, as well as a simple battery model, derived directly from data-sheet characteristics by using polynomial interpolation. The simulation system is completed by a virtual rider and a tool for build test circuits. Results of the simulations on a realistic track are included, to evaluate the different performance of the two strategies in a closed loop environment (thanks to the virtual rider). The results from on-track tests of the real prototype, using the first control strategy, are reported too