Swarm intelligence is an innovative computational way to solving hard pr- lems. This discipline is inspired by the behavior of social insects such as ?sh schools and bird ?ocks and colonies of ants, termites, bees and wasps. In g- eral, this is done by mimicking the behavior of the biological creatures within their swarms and colonies. Particle swarm optimization, also commonly known as PSO, mimics the behaviorofaswarmofinsectsoraschoolof?sh.Ifoneoftheparticlediscovers a good path to food the rest of the swarm will be able to follow instantly even if they are far away in the swarm. Swarm behavior is modeled by particles in multidimensionalspacethathavetwocharacteristics:apositionandavelocity. Theseparticleswanderaroundthehyperspaceandrememberthebestposition that they have discovered. They communicate good positions to each other and adjust their own position and velocity based on these good positions. The ant colony optimization, commonly known as ACO, is a probabilistic technique for solving computational hard problems which can be reduced to ?ndingoptimalpaths.ACOisinspiredbythebehaviorofantsin?ndingshort paths from the colony nest to the food place. Ants have small brains and bad vision yet they use great search strategy. Initially, real ants wander randomly to ?nd food. They return to their colony while laying down pheromone trails. If other ants ?nd such a path, they are likely to follow the trail with some pheromone and deposit more pheromone if they eventually ?nd food.
In Co-Design for System Acceleration, we are concerned with studying the co-design methodology, in general, and how to determine the more suitable interface mechanism in a co-design system, in particular. This will be based on the characteristics of the application and those of the target architecture of the system. We provide guidelines to support the designer's choice of the interface mechanism. The content of Co-Design for System Acceleration is divided into eight chapters. We present co-design as a methodology for the integrated design of systems implemented using both hardware and software components. This includes high-level synthesis and the new technologies available for its implementation. The physical co-design system is then presented. The development route adopted is discussed and the target architecture described. The relation between the execution times and the interface mechanisms is analyzed. In order to investigate the performance of the co-design system for different characteristics of the application and of the architecture, we developed a VHDL model of our co-design system. The timing characteristics of the system are introduced, that is times for parameter passing and bus arbitration for each interface mechanism, together with their handshake completion times. The relation between the coprocessor memory accesses and the interface mechanisms is then studied. Several memory configurations are presented and studied: single-port memory, dual-port memory and cache memory. We also introduce some new trends in co-design and system acceleration.
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