Performance evaluation of Intel and Portland compilers using Intel Westmere processor

In recent years, we have witnessed a growing interest in optimizing the parallel and distributed computing solutions using scaled-out hardware designs and scalable parallel programming paradigms. This interest is driven by the fact that the microchip technology is gradually reaching its physical limitations in terms of heat dissipation and power consumption. Therefore and as an extension to Moore's law, recent trends in high performance and grid computing have shown that future increases in performance can only be reached through increases in systems scale using a larger number of components, supported by scalable parallel programming models. In this paper, we evaluate the performance of two commonly used parallel compilers, Intel and Portland's PGI, using a state-of-the-art Intel Westmere-based HPC cluster. The performance evaluation is based on two sets of experiments, once evaluating the compilers' performance using an MPI-based code, and another using OpenMP. Our results show that, for scientific applications that are matrices-dependant, the MPI and OpenMP features of the Intel compiler supersede PGI when using the defined HPC cluster.