Heterogeneous computing is gaining attention from both industry and academia nowadays. One driving factor for heterogeneous computing is the power efficiency. GPU and FPGA have been reported to achieve much higher power efficiency over CPU on many applications. Comparisons between GPU and FPGA show different characteristics of GPU and FPGA in accelerated computing. Some tasks run better on GPU, some run better on FPGA. Combining GPU and FPGA in one heterogeneous computing platform may provide us the advantages from both sides. This paper presents a heterogeneous computing platform with GPU and FPGA that we have built for power efficient high performance computing. The experimental results of 4 application examples show that different applications have different favorite computing architectures, which suggests a matching of the characteristics between the computation task and the computing architecture is the key to the power efficient high performance computing on heterogeneous computing platforms.