Aiming　at　the　workflow　scheduling　problem　on　CPU-GPU　heterogeneous　systems,　this　article　proposes　a　workflow　scheduling　algorithm　that　optimizes　task　priority　and　processor　selection　phase.　This　article　focuses　on　the　relationship　between　processor　processing　time　and　task　acceleration　ratio,　and　uses　optimistic　finish　time　table.　This　article　estimates　each　task＇s　communication　cost　and　computation　cost　on　the　basis　of　each　task＇s　acceleration　ratio　ri.　Then　the　algorithm　calculates　the　task＇s　priority　ranku　based　on　communication　cost　and　computation　cost.　In　processor　selection　phase,　this　article　takes　the　Earliest　Finish　Time　(EFT)　difference　between　the　processor　with　the　fastest　task　and　the　processor　selected　based　on　Heterogeneous　Earliest　Finish　Time　(HEFT)　algorithm　as　the　judgment　condition　k.　If　the　difference　between　the　earliest　completion　time　of　all　child　tasks　is　greater　than　k,　the　algorithm　selects　the　processor　selected　by　the　HEFT　algorithm;　otherwise,　the　algorithm　selects　another　one.　This　article　uses　the　computational　shared　facility＇s　kernel　timer　for　simulation　experiment,　which　bases　on　the　University　of　Manchester＇s　high　performance　computing　cluster.　Based　on　the　simulation　results,　the　proposed　algorithm　can　reduce　the　maximum　completion　time　and　energy　consumption,　and　improve　the　acceleration　ratio.　Compared　with　the　HEFT　algorithm,　the　task　maximum　completion　time　and　energy　consumption　are　reduced　by　10%　and　5%　respectively,　and　the　acceleration　ratio　is　improved　by　3%.　©　Published　under　licence　by　IOP　Publishing　Ltd.