Empirical performance modeling for parallel weather prediction codes

摘要

Performance modeling for large industrial or scientific codes is of value for program tuning or for selection of new machines when benchmarking is not yet possible. We discuss an em- pirical method of estimating runtime for certain large parallel programs where computational work is estimated by regression functions based on measurements and time cost of commu- nication is modeled by program analysis and benchmarks for communication primitives. The method is demonstrated with the local weather model (LM) of the German Weather Service (DWD) on SP-2, T3E, and SX-4. The method is an economic way of developing performance models because only a moderate number of measurements is required. The resulting model is sufficiently accurate even for very large test cases.