The parallel Fourier pseudospectral method
Journal of Computational Physics
MPI: a message passing interface
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
MPI versus MPI+OpenMP on IBM SP for the NAS benchmarks
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Development and achievement of NAL numerical wind tunnel (NWT) for CFD computations
Proceedings of the 1994 ACM/IEEE conference on Supercomputing
Communication Bandwidth of Parallel Programming Models on Hybrid Architectures
ISHPC '02 Proceedings of the 4th International Symposium on High Performance Computing
An MPI Benchmark Program Library and Its Application to the Earth Simulator
ISHPC '02 Proceedings of the 4th International Symposium on High Performance Computing
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Parallel implementation of 3D global MHD simulations for Earth's magnetosphere
Computers & Mathematics with Applications
Efficient MPI support for advanced hybrid programming models
EuroMPI'10 Proceedings of the 17th European MPI users' group meeting conference on Recent advances in the message passing interface
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The Earth Simulator (ES) is an SMP cluster system. There are two types of parallel programming models available on the ES. One is a flat programming model, in which a parallel program is implemented by MPI interfaces only, both within an SMP node and among nodes. The other is a hybrid programming model, in which a parallel program is written by using thread programming within an SMP node and MPI programming among nodes simultaneously. It is generally known that it is difficult to obtain the same high level of performance using the hybrid programming model as can be achieved with the flat programming model.In this paper, we have evaluated scalability of the code for direct numerical simulation of the Navier-Stokes equations on the ES. The hybrid programming model achieves the sustained performance of 346.9 Gflop/s, while the flat programming model achieves 296.4 Gflop/s with 16 PNs of the ES for a DNS problem size of 2563. For small scale problems, however, the hybrid programming model is not as efficient because of microtasking overhead. It is shown that there is an advantage for the hybrid programming model on the ES for the larger size problems.