Utilizing Graphic Processing Unit(GPU) parallel resource efficiently as the application task of large data quantity deployed on the rapid development CPU+GPU heterogeneous platform became an urgent problem. A task mapping strategy of Multiple Stream-Direction Acyclic Graph(MS-DAG) is proposed, based on the research of task mapping strategy of single GPU. The task mapping strategy for GPU hardware is realized by analyzing the node dependencies in DAG graph, according to the difference of node dependency, dividing reasonable parallel branches and using multi stream pipelining. It shows that the task mapping efficiency of MS-DAG task mapping strategy is about 10% higher than that of Heterogeneous Earliest Finish Time(HEFT) algorithm when the performance of each processor is inconsistent in HEFT algorithm; and the task mapping efficiency of MS-DAG task mapping strategy is 30% higher than that of HEFT algorithm, when the performance of each processor in the HEFT algorithm is consistent.