Abstract
This paper presents an integrated approach to hardware software partitioning and hardware design space exploration. We propose a genetic algorithm which performs hardware software partitioning on a task graph while simultaneously contemplating various design alternatives for tasks mapped to hardware. We primarily deal with data dominated designs typically found in digital signal processing and image processing applications. A detailed description of various genetic operators is presented. We provide results to illustrate the effectiveness of our integrated methodology.
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