Policy-based techniques for self-managing parallel applications

This paper presents an empirical investigation of policy-based self-management techniques for parallel applications executing in loosely-coupled environments. The dynamic and heterogeneous nature of these environments is discussed and the special considerations for parallel applications are identified. An adaptive strategy for the run-time deployment of tasks of parallel applications is presented. The strategy is based on embedding numerous policies which are informed by contextual and environmental inputs. The policies govern various aspects of behaviour, enhancing flexibility so that the goals of efficiency and performance are achieved despite high levels of environmental variability. A prototype self-managing parallel application is used as a vehicle to explore the feasibility and benefits of the strategy. In particular, several aspects of stability are investigated. The implementation and behaviour of three policies are discussed and sample results examined

Self-organising agent communities for autonomic resource management

The autonomic computing paradigm addresses the operational challenges presented by increasingly complex software systems by proposing that they be composed of many autonomous components, each responsible for the run-time reconfiguration of its own dedicated hardware and software components. Consequently, regulation of the whole software system becomes an emergent property of local adaptation and learning carried out by these autonomous system elements. Designing appropriate local adaptation policies for the components of such systems remains a major challenge. This is particularly true where the system’s scale and dynamism compromise the efficiency of a central executive and/or prevent components from pooling information to achieve a shared, accurate evidence base for their negotiations and decisions.In this paper, we investigate how a self-regulatory system response may arise spontaneously from local interactions between autonomic system elements tasked with adaptively consuming/providing computational resources or services when the demand for such resources is continually changing. We demonstrate that system performance is not maximised when all system components are able to freely share information with one another. Rather, maximum efficiency is achieved when individual components have only limited knowledge of their peers. Under these conditions, the system self-organises into appropriate community structures. By maintaining information flow at the level of communities, the system is able to remain stable enough to efficiently satisfy service demand in resource-limited environments, and thus minimise any unnecessary reconfiguration whilst remaining sufficiently adaptive to be able to reconfigure when service demand changes

Making time for great teaching

The report examines the timetables and budgets of six diverse schools across the country to identify ways they can change their practices in order to free up time for teacher development. Overview School education in Australia is slipping. We are falling down the international rankings and our students are performing at a lower level in some subjects than they were a decade ago, according to the OECD. How we respond is vital for our students’ future. High-performing systems around the world know that improving the effectiveness of teaching is the way to lift school performance. They seek to increase the quality – not the quantity – of teaching. They know teaching improves when teachers learn from each other. So they ensure teachers are mentored and teach classes in front of skilled observers, who provide constructive feedback. They make time for teachers to undertake practical research in their schools on how to lift student learning. Governments and many schools have tried to implement similar professional learning programs. But success has been limited. A major stumbling block is finding the resources and time in the school week. Each year we ask schools and teachers to do more. In fact, we need to get them to do less, so they have more time to improve their teaching. This report shows how. We worked extensively with six diverse schools across the country that are striving to give teachers more time. We talked to their teachers and school leaders to develop, fully cost and find time for intensive programs such as intensive mentoring, observation of teachers and feedback on their work, active collaboration and school-based research. Ideally, teachers would have at least three extra school periods a week for these programs. Most of the time can be found by reducing the time teachers spend on ineffective professional development, staff meetings, school assemblies, extra subjects and extra-curricular activities. Schools must make difficult but crucial trade-offs in how teachers and school leaders spend their time. We must be explicit that every time we ask teachers to perform extra activities we are decreasing the quality of teaching and learning in schools. Education strategy must change. Governments must lead the way and prioritise how money is spent at all levels of education. They are still funding ineffective professional learning that lacks accountability. Government regulations restrict schools. Enterprise bargaining agreements restrict changes to work schedules, and duty of care requirements restrain schools that want to free their teachers from child minding to focus on improving teaching. We cannot expect teachers to lift our students to the world’s best while also insisting they spend time on yard duty, pastoral care, and supervising extra-curricular activities. Similarly, we should not follow low-performing systems around the world that have tried to improve schools by decreasing class sizes and increasing the time teachers spend in the classroom. Instead, we must make time for programs that develop teacher skills and deliver great teaching. Some Australian schools, even those with scarce resources and high levels of disadvantage, are making hard choices right now. For the sake of our students all schools and school systems should follow their lead

An approach toward function allocation between humans and machines in space station activities

Basic guidelines and data to assist in the allocation of functions between humans and automated systems in a manned permanent space station are provided. Human capabilities and limitations are described. Criteria and guidelines for various levels of automation and human participation are described. A collection of human factors data is included

Delivering Endogenous Inertia in Prices and Output

This paper presents a DGE model in which aggregate price level inertia is generated endogenously by the optimizing behaviour of price setting ?rms. All the usual sources of inertia are absent here ie., all fi?rms are simultaneously free to change their price once every period and face no adjustment costs in doing so. Despite this, the model generates persistent movements in aggregate output and in?ation in response to a nominal shock. Two modi?cations of a standard one-quarter pre-set price model deliver these results: learning-by-doing and habit formation in leisure.Endogenous price stickiness, Business Cycles, Inflation, Nominal rigidities, Learning-by-doing, Habit formation, Propagation mechanisms, Persistence.

How Do Collegiate Sport Clubs Achieve Organizational Effectiveness?

A greater understanding of the organizational processes of sport clubs can inform strategies to improve clubs’ organizational effectiveness. This study examined whether sport club capacity and activities influence the organizational effectiveness of collegiate sport clubs. Sport club members (n = 201) completed a questionnaire, with secondary data collected from the university. Regression analysis found club operations, club fiscal responsibility, frequency of club practice, and frequency of competitions significantly, positively predict organizational effectiveness. Comparatively, club human capital and facility quality significantly, negatively predict organizational effectiveness. These results have implications relating to club training, mentorship, resource allocation, and club activities

Many-Task Computing and Blue Waters

This report discusses many-task computing (MTC) generically and in the context of the proposed Blue Waters systems, which is planned to be the largest NSF-funded supercomputer when it begins production use in 2012. The aim of this report is to inform the BW project about MTC, including understanding aspects of MTC applications that can be used to characterize the domain and understanding the implications of these aspects to middleware and policies. Many MTC applications do not neatly fit the stereotypes of high-performance computing (HPC) or high-throughput computing (HTC) applications. Like HTC applications, by definition MTC applications are structured as graphs of discrete tasks, with explicit input and output dependencies forming the graph edges. However, MTC applications have significant features that distinguish them from typical HTC applications. In particular, different engineering constraints for hardware and software must be met in order to support these applications. HTC applications have traditionally run on platforms such as grids and clusters, through either workflow systems or parallel programming systems. MTC applications, in contrast, will often demand a short time to solution, may be communication intensive or data intensive, and may comprise very short tasks. Therefore, hardware and software for MTC must be engineered to support the additional communication and I/O and must minimize task dispatch overheads. The hardware of large-scale HPC systems, with its high degree of parallelism and support for intensive communication, is well suited for MTC applications. However, HPC systems often lack a dynamic resource-provisioning feature, are not ideal for task communication via the file system, and have an I/O system that is not optimized for MTC-style applications. Hence, additional software support is likely to be required to gain full benefit from the HPC hardware

Pro-cyclical Solow Residuals without Technology Shocks

Most Real Business Cycle models have a hard time jointly explaining the twin facts of strongly pro-cyclical Solow residuals and extremely low correlations between wages and hours. We present a model that delivers both these results without using exogenous variation in total factor productivity (technology shocks). The key innovation of the paper is to add learning-by-doing to firms technology. As a result firms optimally vary their prices to control the amount of learning which in turn influences future productivity. We show that exogenous variation in labour wedges (preference shocks) measured from aggregate data deliver around fifty percent of the standard deviation in the efficiency wedge (Solow residual) as well as realistic second moments for key aggregate variables which is in sharp contrast to the model without learning-by-doing.Business cycles, Learning-by-Doing, Productivity

Professional Judgment in an Era of Artificial Intelligence and Machine Learning

Though artificial intelligence (AI) in healthcare and education now accomplishes diverse tasks, there are two features that tend to unite the information processing behind efforts to substitute it for professionals in these fields: reductionism and functionalism. True believers in substitutive automation tend to model work in human services by reducing the professional role to a set of behaviors initiated by some stimulus, which are intended to accomplish some predetermined goal, or maximize some measure of well-being. However, true professional judgment hinges on a way of knowing the world that is at odds with the epistemology of substitutive automation. Instead of reductionism, an encompassing holism is a hallmark of professional practice—an ability to integrate facts and values, the demands of the particular case and prerogatives of society, and the delicate balance between mission and margin. Any presently plausible vision of substituting AI for education and health-care professionals would necessitate a corrosive reductionism. The only way these sectors can progress is to maintain, at their core, autonomous professionals capable of carefully intermediating between technology and the patients it would help treat, or the students it would help learn