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The ubiquity of many-core architectures brings challenges in making scalable application software, changing dramatically from the way applications are traditionally developed. Optimization of programs for many-core platforms is a multifaceted problem, where system and architectural factors should be taken into consideration. In this paper, we attack the problem on the aspect of programming paradigm. We propose a hybrid producer-write plus consumer-read shared-memory programming paradigm for implementation of a master-worker video decoder on the TILE64 many-core platform. To evaluate the scalability and performance benefits of different programming paradigms, a Motion JPEG decoder is parallelized using master-worker structure and implemented with combinations of consumer-read programming and producer-write programming. Experimental results show that the proposed implementation obtained competitive performance speedup, scaling well with number of available cores and up to 4 times performance improvement over other implementations on the decoding of a 1080P video.