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Multicore computing platforms have emerged as the most common computing platform to overcome challenges stemming from high power densities and thermal hot spots in conventional microprocessors. However, providing multiple cores does not directly translate into increased performance or better energy efficiency for most applications. The burden is placed on developers and tools to find and exploit parallelism and eventually utilize all of the available computing resources. Since multicore applications are more complex than single core applications, the software development tools play a crucial role to help programmers create high performance and correct software. In this paper we compare the most popular programming models OpenMP, GCD and Pthreads by applying these models to parallelize face detection and automatic speech recognition applications.