A meta-partitioner for faster supercomputer simulations.
Structured adaptive mesh refinement (SAMR) methods are being widely used for computer simulations of various physical phenomena. Parallel implementations potentially offer realistic simulations of complex, three-dimensional applications. But achieving good scalability for large-scale applications is non-trivial. Performance is limited by the partitioners ability to efficiently use the underlying computer's resources. The goal of our research project is to improve scalability for general SAMR applications executing on general parallel computers. We engineer the dynamically adaptive meta-partitioner, able to select and configure the most appropriate partitioning method at run-time, based on system and application state. This presentation gives an overview of our project, reports on recent achievements, and discusses the project's significance in a wider scientific context.
- Research Organization:
- Sandia National Laboratories
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 947263
- Report Number(s):
- SAND2005-1438C
- Country of Publication:
- United States
- Language:
- English
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