Heterogeneous　multi-core　platforms　are　increasingly　prevalent　due　to　perceived　superior　performance　over　homogeneous　systems.　In　order　to　maximize　performance,　each　task　needs　to　be　mapped　to　the　most　appropriate　processor.　This　paper　implements　a　task　allocation　method　based　on　genetic　algorithm.　The　genetic　algorithm　is　used　to　sample　the　application　load　feature　in　the　task　scheduling　time　slice,　and　its　complicated　iterative　process　is　distributed　to　the　following　multiple　scheduling　sampling　periods　to　select　the　core　which　complies　with　its　calculation　characteristic　for　each　task.　Experimental　results　demonstrate　that　the　algorithm　can　effectively　improve　the　system　performance,　compared　with　the　built-in　task　scheduling　mechanism　of　Linux　2.6　kernel.　©　2017　IEEE.