Parallel programming and performance optimization of parallel programs are not simple tasks. Various HPC and OpenMP courses as well as literature serve as introduction to this topic. Assuming the role of HPC beginners we evaluate how far the knowledge acquired from introductory courses and literature can drive performance optimization of a conjugate gradient kernel. We concentrate on OpenMP programming for a large NUMA machine and investigate the new target construct in OpenMP 4.0 to offload to a Xeon Phi coprocessor. We evaluate the final results with a performance model. From these experiences we propose a performance engineering workflow for general use.
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