Parallelizing nested loops on the Intel Xeon Phi on the example of the dense WZ factorization

In this article we evaluate some strategies of parallelizing nested loops on Intel Xeon Phi on the example of the WZ factorization for dense matrices. We employ both parallelism and vectorization to accelerate nested loops on manycore coprocessor. For random dense square matrices with the dominant diagonal we report the execution time and the performance of the nested loops. Numerical experiments show that the vectorization that is efficiently exploiting SIMD vector units do not always improve the application performance on the coprocessor.