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As microprocessors become more complex, early design space exploration plays an essential role in reducing the time to market and post-silicon surprises. The trend toward multi-/many- core processors will result in sophisticated large-scale architecture substrates (e.g. non-uniformly accessed caches interconnected by network-on-chip) that exhibit increasingly complex and heterogeneous behavior. While...
Multi-processor Systems-on-chip are currently designed by using platform-based synthesis techniques. In this approach, a wide range of platform parameters are tuned to find the best trade-offs in terms of the selected system figures of merit (such as energy, delay and area). This optimization phase is called Design Space Exploration (DSE) and it generally consists of a Multi-Objective Optimization...
A neural networks are able to give solutions to complex problems in business intelligence and financial engineering due to their nonlinear processing. This paper consists of a survey of various business intelligence and financial engineering and so on applications based on the neural networks, and also a summary of the recent techniques such as still evolutionary algorithms, cellular computing, Bayesian...
The neural network model presents a new procedure and structure in nonlinear interpolation and demonstrates a potential of stock market prediction with incomplete, imprecise and noisy data. However, a random selection of model parameters might cause the ??over-fitting?? or ??under-fitting?? problem in generalization or prediction. This paper presents a sensitivity analysis of optimal hidden layers...
The ultimate goal of computer design is to satisfy the end-user. In particular computing domains, such as interactive applications, there exists a variation in user expectations and user satisfaction relative to the performance of existing computer systems. In this work, we leverage this variation to develop more efficient architectures that are customized to end-users. We first investigate the relationship...
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