Traditionally, at early design stages, leakage power is associated with the number of transistors in a design. Hence, intuitively an implementation with minimum resource usage would be best for low leakage. Such an allocation would generally be followed by switching optimal resource binding to achieve a low power design. This treatment of leakage power is unaware of operating conditions such as temperature. In this paper, we propose a technique to reduce the total leakage power of a design by identifying the optimal number of resources during allocation and binding. We demonstrate that, contrary to the general tendency to minimize the number of resources, the best solution can actually be achieved if a certain degree of redundancy is allowed. This is due to the fact that leakage is strongly dependent on the on-chip temperature profile. Distributing activity over a higher number of resources can reduce power density, remove potential hotspots and subsequently minimize thermal induced leakage. On the other hand, using an arbitrarily high number of resources will not yield the best solution. In this paper, we show that there is a power density, hence, temperature, at which the total leakage power will reach its optimal value. Such an optimal resource number can be a better starting point for the subsequent switching-driven low power binding. We also present a high-level power density-aware leakage model. Based on the estimates by this model, we optimize the total leakage power by 53.8% on average compared to the minimum resource binding, and 35.7% on average compared to a temperature-aware resource binding technique.
With the development of modern society, network marketing has become an important business models. In order to build an effective shopping website interface layout design visual assessment method, and promote the standardization of website interface layout design, in this study, using eye tracking technology and statistical methods, to get the viewed hotspots and browsing habits of the subjects., then analyzed the rationality of shopping website interface layout , to provide scientific reference for website interface layout design.
This article provides a whole solution to the battery manufacturing execution system (MES) which realizes the complete control of data in battery manufacturing . MES can improve the manufacturing efficiency. Along with many other functions like quality trace, production planning, quality management, production status monitoring, production tracking, profit forecast predicting profit, recording of exceptional production, raw material management, equipment management, report printing etc .To remain competitive, manufacturers need MES solutions that meet their industry-specific needs. All the functions turn the battery manufacturing execution system into a production, management, decision-making supporting system which combines work flow, data flow and control flow.
Design Factors of product-family is one of the important elements to maintain and to improve customers’ loyalty to a band. Extraction of design factors of product family based on customer needs promotes relations between brands and customers while improves satisfaction to products of the consumers. In existing studies, methods of getting customer needs have always attracted close attention. But the links between customer needs and design factors have not been adequately studied. By using QFD (Quality Function Deployment) and increasing the number of cascaded transformation hierarchies of the House of Quality, the method of extracting design factors of product family is proposed in this paper.
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