Abstract In this paper we evaluate the performance of Unified Parallel C (which implements the partitioned global address space programming model) using a numerical method that is widely used in fluid dynamics. In order to evaluate the incremental approach to parallelization (which is possible with UPC) and its performance characteristics, we implement different levels of optimization of the UPC code and compare it with an MPI parallelization on four different clusters of the Austrian HPC infrastructure (LEO3, LEO3E, VSC2, VSC3) and on an Intel Xeon Phi. We find that UPC is significantly easier to develop in compared to MPI and that the performance achieved is comparable to MPI in most situations. The obtained results show worse performance (on VSC2), competitive performance (on LEO3, LEO3E and VSC3), and superior performance (on the Intel Xeon Phi) compared with MPI.
Whereas most applications in the realm of the partitioned global address space make use of PGAS languages we here demonstrate an implementation on top of a PGAS-API. In order to improve the scalability of the unstructured CFD solver TAU we have implemented an asynchronous communication strategy on top of the PGAS-API of GPI. We have replaced the bulk-synchronous two-sided MPI exchange with an asynchronous, RDMA-driven, one-sided communication pattern. We also have developed an asynchronous shared memory strategy for the TAU solver. We demonstrate that the corresponding implementation not only scales one order of magnitude higher than the original MPI implementation, but that it also outperforms the hybrid OpenMP MPI programming model.