Abstract
The broad introduction of multi-core platforms into computing has brought a great opportunity to develop computationally demanding applications such as matrix computations on parallel computing platforms. Basic matrix computations such as vector and matrix addition, dot product, outer product, matrix transpose, matrix - vector and matrix multiplication are very challenging computational kernels arising in scientific computing. In this paper, we parallelize those basic matrix computations using the multicore and parallel programming tools. Specifically, these tools are Pthreads, OpenMP, Intel Cilk++, Intel TBB, Intel ArBB, SMPSs, SWARM and FastFlow. The purpose of this paper is to present a quantitative and qualitative study of these tools for parallel matrix computations. 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.
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