Different parallelization methods vary in their system requirements, programming styles, efficiency of exploring parallelism, and the application characteristics they can handle. For different situations, they can exhibit totally different performance gains. This paper compares OpenMP, MPI, and Strings for parallelizing a complicated tribology problem. The problem size and computing infrastructure is changed to assess the impact of this on various parallelization methods. All of them exhibit good performance improvements and it exhibits the necessity and importance of applying parallelization in this field.
|Number of pages||21|
|Journal||Journal of Supercomputing|
|State||Published - Jun 2004|
- Distributed shared memory
- Molecular dynamics