Heterogeneous many-core processors become an important trend in high-performance computing area, but the issue that the sophisticated architecture complicates the programming is more significantly. To solve this problem, this study proposes a parallelizing compilation framework for heterogeneous many-core processors based on the open source Open64 compiler, automating the transformation from a sequential program to heterogeneous parallel code. The framework mainly comprises a work scheduling module that identifies the parallelizable regions and achieves a multi-dimensional parallelization recognition for nested loops; a data mapping module that maps data between the main memory and SPM and realizes array boundary analysis and pointer range analysis; a transmission optimizing module that implements optimizations by merging, hoisting and packaging data transmission, and transposing array; and a performance estimation module that proposes a dynamic-static hybrid method to analyze benefit based on the cost model for SW26010. The compilation framework is implemented on top of Sunway SW26010 processors, and experimental evaluations are conducted on numerous benchmarks. The experimental results show that the proposed framework can parallelize these applications and obtain a promising performance improvement on heterogeneous many-core platforms.