Combining CBR and GA for designing FPGAs

Field programmable gate arrays (FPGAs) are a form of user-programmable logic devices that contain an array of logic gates. As there is no complete set of techniques for designing any FPGA program, researchers have been successful in evolving program designs using genetic algorithms (GAs). However, using GAs to generate software programs for FPGAs faces two main problems, namely scaling and errors. In this paper, we present our on-going research towards overcoming these problems by the integration of GAs with case-based reasoning (CBR). CBR is a problem-solving method that reuses old solutions to solve new problems. Our research work aims to apply CBR to reuse genetically evolved FPGA programs in order to develop larger programs at a reasonable computational expense. This paper describes our preliminary experiments and their results, which are encouraging