Monitoring Performance and Power for Application Characterization with the Cache-Aware Roofline Model

Abstract

Accurate on-the-fly characterization of application behaviour requires assessing a set of execution-related parameters at runtime, including performance, power and energy consumption. These parameters can be obtained by relying on hardware measurement facilities built-in modern multi-core architectures, such as performance and energy counters. However, current operating systems (OSs) do not provide the means to directly obtain these characterization data. Thus, the user needs to rely on complex custom-built libraries with limited capabilities, which might introduce significant execution and measurement overheads. In this work, we propose two different techniques for efficient performance, power and energy monitoring for systems with modern multi-core CPUs. Here we propose two monitoring tools that allow capturing the run-time behaviour of a wide range of applications at different system levels: (i) at the user-space level, and (ii) at kernel-level, by using the OS scheduler to directly capture this information. Although the importance of the proposed monitoring facilities is patent for many purposes, we focus herein on their employment for application characterization with the recently proposed Cache-aware Roofline model.