A Parallel Programming Model Research Based on Heterogeneous Multi-core Embedded Processor

Today is the era of information explosion, efficient methods for massive data processing are becoming a hotspot. MapReduce is a popular parallel programming model and widely used in large-scale data parallel computing. This paper proposes a parallel programming model based on heterogeneous multi-core embedded processor. On the base of ordinary computer completing computing, we make optimization and improvement, and use the method of combining embedded dual-core ARM processors with multiple high performance FPGAs to complete complex processing. Xilinx Zynq device is used as the hardware platform. By selecting Sobel image processing, histogram, matrix multiply and illumination enhancement cases, we test the parallel programming model. The results show that the speedup is 84.62x versus CPU-based implementation. In addition, it is proven that this parallel programming model is suitable for the CPU-FPGA heterogeneous system which can be used as cluster cloud computing node. Meanwhile, we make a comparison of our model with other references and verify the efficient of the programming model in this paper.