Hardware/software　(HW/SW)　partitioning　is　to　determine　which　components　of　a　system　are　implemented　on　hardware　and　which　ones　on　software.　It　is　one　of　the　most　important　steps　in　the　design　of　embedded　systems.　The　HW/SW　partitioning　problem　is　an　NP-hard　constrained　binary　optimization　problem.　In　this　paper,　we　propose　a　tabu　search-based　memetic　algorithm　to　solve　the　HW/SW　partitioning　problem.　First,　we　convert　the　constrained　binary　HW/SW　problem　into　an　unconstrained　binary　problem　using　an　adaptive　penalty　function　that　has　no　parameters　in　it.　A　memetic　algorithm　is　then　suggested　for　solving　this　unconstrained　problem.　The　algorithm　uses　a　tabu　search　as　its　local　search　procedure.　This　tabu　search　has　a　special　feature　with　respect　to　solution　generation,　and　it　uses　a　feedback　mechanism　for　updating　the　tabu　tenure.　In　addition,　the　algorithm　integrates　a　path　relinking　procedure　for　exploitation　of　newly　found　solutions.　Computational　results　are　presented　using　a　number　of　test　instances　from　the　literature.　The　algorithm　proves　its　robustness　when　its　results　are　compared　with　those　of　two　other　algorithms.　The　effectiveness　of　the　proposed　parameter-free　adaptive　penalty　function　is　also　shown.