Comparison of Parallel Programming Models on Clusters of SMP Nodes

Most HPC systems are clusters of shared memory nodes. Parallel programming must combine the distributed memory parallelization on the node interconnect with the shared memory parallelization inside of each node. Various hybrid MPI+OpenMP programming models are compared with pure MPI. Benchmark results of several platforms are presented. This paper analyzes the strength and weakness of several parallel programming models on clusters of SMP nodes. There are several mismatch problems between the (hybrid) programming schemes and the hybrid hardware architectures. Benchmark results on a Myrinet cluster and on recent Cray, NEC, IBM, Hitachi, SUN and SGI platforms show, that the hybridmasteronly programming model can be used more efficiently on some vector-type systems, but also on clusters of dual-CPUs. On other systems, one CPU is not able to saturate the inter-node network and the commonly used masteronly programming model suffers from insufficient inter-node bandwidth. This paper analyses strategies to overcome typical drawbacks of this easily usable programming scheme on systems with weaker inter-connects. Best performance can be achieved with overlapping communication and computation, but this scheme is lacking in ease of use.