| Abstract: | This research defines and analyzes a methodology for deriving a performance model for SPMD hybrid parallel applications. Hybrid parallelism combines shared memory and message passing computing models. This work extends the current practice of application performance modelling by development of a methodology for hybrid applications with these procedures. - Creation of a model based on complexity analysis of an application code and its data structures.
- Enhancement of a static complexity model by dynamic factors to capture execution time phenomena, such as memory hierarchy effects.
- Quantitative analysis of model characteristics and the effects of perturbations in measured parameters.
These research results are presented in the context of a hybrid parallel implementation of a sparse linear algebra kernel. A model for this kernel is derived and analyzed using the methodology. Application of the model on two large parallel computing platforms provides case studies for the methodology. Operating system issues, machine balance factor, and memory hierarchy effects on model accuracy are examined. Copyright © 2007 John Wiley & Sons, Ltd. |
