Search Results for « Performance »

Software systems continuously evolve due to new functionalities, requirements, or maintenance activities. In the context of software evolution, software refactoring has gained a strategic relevance. The space of possible software refactoring is usually very large, as it is given by the combinations of different refactoring actions that can produce software system alternatives. Multi-objective algorithms have shown the ability to discover alternatives by pursuing different objectives simultaneously. Performance of such algorithms in the context of software model refactoring is of paramount importance. Therefore, in this paper, we conduct a performance analysis of three genetic algorithms to compare them in terms of performance and quality of solutions. Our results show that there are significant differences in performance among the algorithms (e.g., PESA2 seems to be the fastest one, while NSGA-II shows the least memory usage).

Selection can be measured in natural populations by the changes it causes in the means, variances and covariances of phenotypic characters. Furthermore the force of selection can be measured in conventional statistical terms that also play a key role in theoretical equations for evolutionary change. The problem of measuring selection on morphological traits is simplified by breaking the task into two parts: measurement of the effects of morphological variation on performance and measurement of the effects of performance on fitness. The first part can be pursued in the laboratory but the second part is best accomplished in the field. The approach is illustrated with a hypothetical analysis of selection acting on the complex trophic morphology of snakes.

Multiprocessor task scheduling is an important and computationally difficult problem. This paper proposes a comparison study of genetic algorithm and list scheduling algorithm. Both algorithms are naturally parallelizable but have heavy data dependencies. Based on experimental results, this paper presents a detailed analysis of the scalability, advantages and disadvantages of each algorithm. Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uni-processor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given task should execute. In multiprocessor systems, an efficient scheduling of a parallel program onto the processors that minimizes the entire execution time is vital for achieving a high performance. This scheduling problem is known to be NP- Hard. In multiprocessor scheduling problem, a given program is to be scheduled in a given multiprocessor system such that the program's execution time is minimized. The last job must be completed as early as possible. Genetic algorithm (GA) is one of the widely used techniques for constrained optimization.

The complexity of multimedia applications in terms of intensity of computation and heterogeneity of treated data led the designers to embark them on multiprocessor systems on chip. The complexity of these systems on one hand and the expectations of the consumers on the other hand complicate the designers job to conceive and supply strong and successful systems in the shortest deadlines. They have to explore the different solutions of the design space and estimate their performances in order to deduce the solution that respects their design constraints. In this context, we propose the modeling of one of the design space possible solutions: the software to hardware task migration. This modeling exploits the synchronous dataflow graphs to take into account the different migration impacts and estimate their performances in terms of throughput.

This article discusses the relation of self-efficacy to motivation and performance in cognitive and sport domains. Self-efficacy refers to one's beliefs about accomplishing a task and can influence choice of activities. effort, persistence. and achievement. People enter activities with varying levels of self-efficacy derived from prior experience, personal qualities, and social support. As they work on tasks they acquire information about how well they are doing. This information influences their self-efficacy for continued learning and performance. Research is described in which interventions involving models, goal setting, and feedback, were employed to affect self-efficacy. Regardless of domain, research shows that self-efficacy helps to predict motivation and performance. and studies testing causal models highlight the important role played by self-efficacy. Suggestions for future research are given, along with implications of theory and research for education and training.

The term "performance portability" has been informally used in computing to refer to a variety of notions which generally include: 1) the ability to run one application across multiple hardware platforms; and 2) achieving some notional level of performance on these platforms. However, there has been a noticeable lack of consensus on the precise meaning of the term, and authors' conclusions regarding their success (or failure) to achieve performance portability have thus been subjective. Comparing one approach to performance portability with another has generally been marked with vague claims and verbose, qualitative explanation of the comparison. This paper presents a concise definition for performance portability, along with a simple metric that accurately captures the performance and portability of an application across different platforms. The utility of this metric is then demonstrated with a retroactive application to previous work.

Negotiating Performance Diana Taylor Para esta conferencia dedicada al teatro latinoamericano, George Woodyard me asignó la tarea de hablar acerca de "Performance."Esto me interesó muchísimo; de hecho Juan Villegas y yo estamos editando un libro sobre el asunto titulado Negotiating Performance.Pero ya de entrada el tema me presentó dos problemas interesantes.Para empezar, la palabra "performance" en inglés tiene varios sentidos contradictorios.Más problemático aún es que no existe la palabra equivalente a "performance" en español.El concepto teórico que a mí me interesa discutir aquí aún no se ha analizado sistemáticamente en nuestro campo y nos falta un vocabulario adecuado para hacerlo.Pues bien, me dije, daré la ponencia en inglés y ya está.(Fue durante esta etapa que propuse el título en inglés que ven en el programa.)Pero después de reflexionar un poco más, se me hizo importante iniciar aquí un dialogo acerca de los múltiples sentidos de la palabra "performance" ya que, aunque nos falte el vocabulario, el fenómeno mismo tiene una larga y rica tradición en nuestras culturas que, simplemente, no se ha teorizado.Quisiera explorar las nuevas posibilidades teóricas que nos ofrece el concepto en nuestras labores como teatristas y como latinos/as o latinoamericanistas y dar un par de ejemplos de Negotiating Performance del tipo de investigación que nos permite realizar.En inglés, "performance" se ha utilizado generalmente para referirse a dos fenómenos que son esencialmente antitéticos.En su sentido más común, la palabra se podría traducir como puesta escénica o mise en scene.Si el teatro se considera un arte híbrido-texto y espectáculo-performance se definiría en oposición al texto dramático, un sub-género teatral.En su otro sentido, performance ha llegado a significar casi lo opuesto de teatro; se ha independizado para constituirse en diversas formas anti-teatrales que resisten categorización: performance art, public art, instalaciones vivas, etcétera.En teoría, performance art rechaza la institucionalización del teatro e intenta subvertir un sistema de representaciones acusado de ser cómplice de un sistema social represivo.En esta ponencia, me interesa explorar no sólo este segundo fenómeno sino también un tercer sentido de performance que abarca, pero va más allá de

The performance of cluster computing depends on how concurrent jobs share multiple data center resource types like CPU, RAM and disk storage. Recent research has discussed efficiency and fairness requirements and identified a number of desirable scheduling objectives including so-called dominant resource fairness (DRF). We argue here that proportional fairness (PF), long recognized as a desirable objective in sharing network bandwidth between ongoing flows, is preferable to DRF. The superiority of PF is manifest under the realistic modelling assumption that the population of jobs in progress is a stochastic process. In random traffic the strategy-proof property of DRF proves unimportant while PF is shown by analysis and simulation to offer a significantly better efficiency-fairness tradeoff.

This article approaches translanguaging from the perspective of performance as theorised in anthropological and sociological studies. Drawing on the key argument that every facet of social reality is a performance, and social interaction is based on tacit agreement among all the participants, the article aims to make sense of a key participant’s making sense of her social world, based on an ethnographic investigation into the work and life of a multilingual, London-based artist of Polish origin. It discusses the creative and critical interpretative potentials that break down the boundaries of performance vs. everyday life, the observer vs. the observed, and the researcher vs. the researched. It also calls for further attention to the performative aspects of translanguaging.