Performance Behavior Prediction Scheme for Shared-Memory Parallel Applications

Abstract

A current challenge in computing centers with different clusters to run applications is which multicore systems must we choose to run a given shared-memory parallel application. Our proposal is to generate a node performance profile database (NPPDB), composed by performance profiles given by distinct micro benchmark-target node combination. Then, applications are executed on a base node to identify different execution phases and their weights, and to collect performance and functional data for each phase. For similarity, the information to compare behavior is always obtained on the same node. When we want to project performance behavior, we look for similarity using the information from the performance profiles database with the phase characterization, in order to select the appropriate node for running the application.