We use three Parallel Research Kernels to compare performance of a set of programming models(We employ the term programming model as it is commonly used in the application community. A more accurate term is programming environment, which is the collective of abstract programming model, embodiment of the model in an Application Programmer Interface (API), and the runtime that implements it.): MPI1 (MPI two-sided communication), MPIOPENMP (MPI+OpenMP), MPISHM (MPI1 with MPI-3 interprocess shared memory), MPIRMA (MPI one-sided communication), SHMEM, UPC, Charm++ and Grappa. The kernels in our study - Stencil, Synch_p2p and Transpose - underlie a wide range of computational science applications. They enable direct probing of properties of programming models, especially communication and synchronization. In contrast to mini- or proxy applications, the PRK allow for rapid implementation, measurement and verification. Our experimental results show MPISHM the overall winner, with MPI1, MPIOPENMP and SHMEM performing well. MPISHM and MPIOPENMP outperform the other models in the strong-scaling limit due to their effective use of shared memory and good granularity control. The non-evolutionary models Grappa and Charm++ are not competitive with traditional models (MPI and PGAS) for two of the kernels; these models favor irregular algorithms, while the PRK considered here are regular.
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