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This paper implements basic computational kernels of the scientific computing such as matrix - vector product, matrix product and Gaussian elimination on multi-core platforms using several parallel programming tools. Specifically, these tools are Pthreads, OpenMP, Intel Cilk++, Intel TBB, Intel ArBB, SMPSs, SWARM and Fast Flow. The aim of this paper is to present an unified quantitative and qualitative study of these tools for parallel computation of scientific computing kernels on multicore. Finally, based on this study we conclude that the Intel ArBB and SWARM parallel programming tools are the most appropriate because these give good performance and simplicity of programming.