Parallel Application Signature for Performance Analysis and Prediction

Predicting the performance of parallel scientific applications is becoming increasingly complex. Our goal was to characterize the behavior of message-passing applications on different target machines. To achieve this goal, we developed a method called parallel application signature for performance prediction (PAS2P), which strives to describe an application based on its behavior. Based on the application´s message-passing activity, we identified and extracted representative phases, with which we created a parallel application signature that enabled us to predict the application´s performance. We experimented with using different scientific applications on different clusters. We were able to predict execution times with an average accuracy greater than 97 percent.