Verification of the Extended Roofline Model for Asynchronous Many Task Runtimes

Abstract

Asynchronous Many Task (AMT) runtimes promise application designers the ability to better utilize novel hardware resources and to take advantages of the idle times that might arise from the discrepancies due to mismatches between software and hardware components. To foresee possible problems between hardware and software components (described as mismatches), designers usually use models to predict and analyze application behaviors. However, current models are ill suited for the AMT crowd because of its dynamic behavior and agility. To this effect, we developed an extended roofline model that aims to provide upper bounds on execution for AMT frameworks. This work focuses on the validation and error characterization of this model using different statistical techniques and a large set of experiments to evaluate and characterize its error and its sources. We found out that in the worst case, the error can grow to an order of magnitude, however there are several techniques to increase the model accuracy given a machine configuration.