Static Performance Prediction in PCASE: A Programming Environment for Parallel Supercomputers

This paper presents a performance estimator, a prototype of which is implemented within the parallel programming environment PCASE. The estimation is based on static performance prediction, using not only the design information of target machines but also benchmarking results. Additionally, communication costs are estimated based on a hierarchical memory machine model, which enables users to understand all the underlying communication costs on distributed memory machines for each parallel loop. With this performance suggestion, it is possible to interactively optimize data distribution and appropriately select vectorized or parallelized loops. Moreover, the skeleton profiling method is presented. It makes high speed trace (execution count of each statement) generation possible by deleting statements which do not affect the execution path of a program.