A Microbenchmark Suite for Mixed-Mode OpenMP/MPI

Authors:
J. Mark Bull;James P. Enright;Nadia Ameer
Affiliations:
EPCC, The King's Buildings, The University of Edinburgh, Edinburgh, Scotland, U.K. EH9 3JZ;EPCC, The King's Buildings, The University of Edinburgh, Edinburgh, Scotland, U.K. EH9 3JZ;EPCC, The King's Buildings, The University of Edinburgh, Edinburgh, Scotland, U.K. EH9 3JZ
Venue:
IWOMP '09 Proceedings of the 5th International Workshop on OpenMP: Evolving OpenMP in an Age of Extreme Parallelism
Year:
2009

Citing 4
Cited 2

Dual-level parallelism for ab initio molecular dynamics: Reaching teraflop performance with the CPMD code

Parallel Computing
Development of mixed mode MPI / OpenMP applications

Scientific Programming
SKaMPI: a comprehensive benchmark for public benchmarking of MPI

Scientific Programming
Hybrid MPI/OpenMP Parallel Programming on Clusters of Multi-Core SMP Nodes

PDP '09 Proceedings of the 2009 17th Euromicro International Conference on Parallel, Distributed and Network-based Processing

Enabling low-overhead hybrid MPI/OpenMP parallelism with MPC

IWOMP'10 Proceedings of the 6th international conference on Beyond Loop Level Parallelism in OpenMP: accelerators, Tasking and more
Performance metrics in a hybrid MPI-OpenMP based molecular dynamics simulation with short-range interactions

Journal of Parallel and Distributed Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

With the current prevalence of multi-core processors in HPC architectures, mixed-mode programming, using both MPI and OpenMP in the same application, is becoming increasingly important. However, no low-level synthetic benchmarks exist to test the performance of this programming model. We have designed and implemented a set of microbenchmarks for mixed-mode programming, including both point-to-point and collective communication patterns. These microbenchmarks have been run on a number of current HPC architectures: the results show some interesting performance differences between the architectures and highlight some possible inefficiencies in the implementation of MPI on multi-core systems.