Fitness inheritance in evolutionary and multi-objective high-level synthesis

Abstract—The high-level synthesis process allows the automatic design and implementation of digital circuits starting from a behavioral description. Evolutionary algorithms are very widely adopted to approach this problem or just part of it. Neverthless, some concerns regarding execution times exist. In evolutionary high-level synthesis, design solutions have to be evaluated to extract information about some figures of merit (such as performance, area, etc.) and to allow the genetic algorithm to evolve and converge to Pareto-optimal solutions. Since the execution time of such evaluations increases with the complexity of the specification, the overall methodology could lead to unacceptable execution time. This paper presents a model to exploit fitness inheritance in a multi-objective optimization algorithm (i.e. NSGA-II) by substituting the expensive real evaluations with estimations based on closeness in an hypothetical design space. The estimations are based on the measure of the...

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Christian Pilato, Gianluca Palermo, Antonino Tumeo, Fabrizio Ferrandi, Donatella Sciuto, Pier Luca Lanzi
• Keywords: Artificial Intelligence, CEC 2007, Concerns Regarding Execution, Execution Time, Unacceptable Execution Time