Multilevel algorithms for multi-constraint graph partitioning
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
A parallel rendezvous algorithm for interpolation between multiple grids
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
Using MPI-2: Advanced Features of the Message Passing Interface
Using MPI-2: Advanced Features of the Message Passing Interface
Numerical Modeling in Applied Physics and Astrophysics
Numerical Modeling in Applied Physics and Astrophysics
A New Algorithm for Multi-objective Graph Partitioning
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
Graph partitioning for high-performance scientific simulations
Sourcebook of parallel computing
Parallel Flux Sweep Algorithm for Neutron Transport on Unstructured Grid
The Journal of Supercomputing
Multi-Constraint Mesh Partitioning for Contact/Impact Computations
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
Towards a parallel framework of grid-based numerical algorithms on DAGs
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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Complex physical phenomena can be usually split into several interacting physical computational models and can be numerically simulated by coupling parallel codes individually designed for these models. Besides rational splitting and efficient numerical methods for different models, we must design scalable parallel algorithms to concatenate these parallel codes. Meanwhile, three objectives should be well balanced. The first is how to efficiently transfer data among multiple physical models, the second is how to inherit original scalability of parallel codes and then ensure good scalability of full simulation, and the third is how to ensure independent or simultaneous developments of codes by different research groups. This paper presents two concatenation algorithms for parallel numerical simulation of radiation hydrodynamics coupled with neutron transport on unstructured grid. The first, Full Loose Concatenation Algorithm, focuses on independent development and inheritance of original scalability, and the second, Two Level Compact Concatenation Algorithm, focuses on optimal tradeoff among above three objectives. Theoretical analysis for communicational complexity and parallel numerical experiments using hundreds of processors on two parallel machines have shown that these two algorithms are efficient and can be generalized to other parallel numerical simulations for hydrodynamics coupled with radiation or neutron transport. In particular, the second algorithm is linearly scalable and has achieved theoretical optimal performance.