Abstract:
Using a data-parallel strategy to parallelize molecular dynamics programs makes it possible to simulate very large molecules on large numbers of processors. Applying on a...Show MoreMetadata
Abstract:
Using a data-parallel strategy to parallelize molecular dynamics programs makes it possible to simulate very large molecules on large numbers of processors. Applying on appropriate combination of data partitioning and iteration distribution algorithms not only optimizes communication overheads but also achieves good load balance, and hence good performance.<>
Published in: IEEE Computational Science and Engineering ( Volume: 2, Issue: 2, Summer 1995)
DOI: 10.1109/99.388949
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Molecular Dynamics ,
- Molecular Dynamics Program ,
- Time Step ,
- Atomic System ,
- Communication Overhead ,
- Decomposition Algorithm ,
- Design Philosophy ,
- Number Of Processors ,
- Reduction In Execution Time ,
- Spatial Decomposition ,
- National Institutes Of Health ,
- Computation Time ,
- Computer Science ,
- Atomic Positions ,
- Array Data ,
- High-performance Computing ,
- Computational Load ,
- Non-bonded Interactions ,
- Data Partitioning ,
- Computational Work ,
- Load Balancing ,
- Force Matrix ,
- Communication Volume ,
- Regular Distribution ,
- Communication Time ,
- Cut-off Range ,
- Communication Cost ,
- Parallel Efforts ,
- High Communication
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Molecular Dynamics ,
- Molecular Dynamics Program ,
- Time Step ,
- Atomic System ,
- Communication Overhead ,
- Decomposition Algorithm ,
- Design Philosophy ,
- Number Of Processors ,
- Reduction In Execution Time ,
- Spatial Decomposition ,
- National Institutes Of Health ,
- Computation Time ,
- Computer Science ,
- Atomic Positions ,
- Array Data ,
- High-performance Computing ,
- Computational Load ,
- Non-bonded Interactions ,
- Data Partitioning ,
- Computational Work ,
- Load Balancing ,
- Force Matrix ,
- Communication Volume ,
- Regular Distribution ,
- Communication Time ,
- Cut-off Range ,
- Communication Cost ,
- Parallel Efforts ,
- High Communication