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Modern computer architectures have increased their paces to move into heterogeneity by integrating specialized processing elements such as GPUs, FPGAs, DSPs into a single system together with general processors. The integration allows developers to maximize their applications performance by mapping the different modules to different processing elements based on the characteristics. However, the current programming models are not comprehensive, portable or expressive enough to support developers' needs. In this paper, we are exploring the current programming approach on heterogeneous embedded systems, as well as studying the popular shared memory programming model OpenMP for how to adapt it to heterogeneous systems. We present our initial design of OpenMP extensions to support work distribution and data communication between different processing elements.
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