A Framework to Develop Symbolic Performance Models of Parallel Applications
- ORNL
Performance and workload modeling has numerous uses at every stage of the high-end computing lifecycle: design, integration, procurement, installation and tuning. Despite the tremendous usefulness of performance models, their construction remains largely a manual, complex, and time-consuming exercise. We propose a new approach to the model construction, called modeling assertions (MA), which borrows advantages from both the empirical and analytical modeling techniques. This strategy has many advantages over traditional methods: incremental construction of realistic performance models, straightforward model validation against empirical data, and intuitive error bounding on individual model terms. We demonstrate this new technique on the NAS parallel CG and SP benchmarks by constructing high fidelity models for the floating-point operation cost, memory requirements, and MPI message volume. These models are driven by a small number of key input parameters thereby allowing efficient design space exploration of future problem sizes and architectures.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- DE-AC05-00OR22725
- OSTI ID:
- 989553
- Resource Relation:
- Conference: 5th International Workshop on Performance Modeling, Evaluation, and Optimization of Parallel and Distributed Systems, Rhodes, Greece, 20060429, 20060429
- Country of Publication:
- United States
- Language:
- English
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