Sharif Digital Repository

Network-on-Chips are now the popular communication medium to support inter-IP communications in complex on-chip systems with tens to hundreds IP cores. Higher scalability (compared to the traditional shared bus and point-to-point interconnects), throughput, and reliability are among the most important advantages of NoCs. Moreover, NoCs can well match current CAD methodologies mainly relying on modular and reusable structures with regularity of structural pattern. However, since NoCs are resource-limited, determining how to distribute application load over limited on-chip resources (e.g. switches, buffers, virtual channels, and wires) in order to improve the metrics of interest and satisfy... 

In this paper, we introduce a new Multi-Objective Genetic Algorithm (MOGA) for mapping a given set of intellectual property onto a Network-on-Chip architecture such that for a specific application total communication cost and energy consumption become optimized while bandwidth constraints are satisfied. As the main theoretical contribution, we first introduce a generic queuing model to estimate performance and an experimental energy consumption model during the design phase, with acceptable accuracy. Then, an efficient genetic algorithm employs these models to propose a Pareto optimal front for an application and an arbitrary topology. Experimental results show that the proposed algorithm is... 

In most image retrieval systems, images include various high-level semantics, called tags or annotations. Virtually all the state-of-the-art image annotation methods that handle imbalanced labeling are search-based techniques which are time-consuming. In this paper, a novel coupled dictionary learning approach is proposed to learn a limited number of visual prototypes and their corresponding semantics simultaneously. This approach leads to a real-time image annotation procedure. Another contribution of this paper is that utilizes a marginalized loss function instead of the squared loss function that is inappropriate for image annotation with imbalanced labels. We have employed a marginalized...