In　recent　years,　with　the　development　of　processor　architecture,　heterogeneous　processors　including　CPUs　and　GPUs　have　become　mainstream　processors.　In　order　to　take　full　advantage　of　the　computing　power　of　heterogeneous　cores,　it　is　necessary　to　maintain　workload　balance　between　heterogeneous　cores　while　the　system　is　executing　applications.　And　it　is　also　important　to　optimize　the　efficiency　of　the　application　execution　on　the　GPU　by　improving　the　thread　organization.　In　order　to　improve　performance,　we　propose　a　block　size　adjustment　strategy　that　adapts　to　the　current　application　and　GPU　environment.　Based　on　this,　we　propose　a　strategy　for　balancing　CPU-GPU　workload　that　preferentially　protects　the　core.　These　strategies　optimize　the　execution　time　of　applications　on　CPU-GPU　heterogeneous　platforms.　Finally,　we　tested　the　actual　effect　of　the　strategy　by　running　four　benchmarks　in　a　CPU-GPU　heterogeneous　environment.　The　experimental　results　show　that　the　performance　can　be　significantly　improved　by　block　size　adjustment　and　workload　balancing　strategy.　These　two　strategies　reduce　application　execution　time　by　up　to　26.21%　and　58.01%,　respectively,　compared　to　GPU-only　execution　time.　©　2019　IEEE.