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Performance and Energy Monitoring Tools for Modern Processor Architectures
| Content Provider | Semantic Scholar |
|---|---|
| Author | Filipe, Luís Taniça, Mataloto Antão, Diogo |
| Copyright Year | 2014 |
| Abstract | Accurate on-the-fly characterization of application behavior requires assessing a set of execution-related parameters at run-time, 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 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 tools for efficient performance, power and energy monitoring of systems with modern multi-core CPUs, that allow capturing the run-time behavior 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 Cache-aware Roofline model. The experimental results show the capabilities of the proposed tools to deliver detailed and accurate information about the behavior of real-world applications on the underlying architectural resources. Moreover, they allow reconstructing and identifying the execution patterns of the profiled benchmarks from standard suites (SPEC CPU2006), while introducing negligible overheads. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://fenix.tecnico.ulisboa.pt/downloadFile/395146439693/thesis.pdf |
| Alternate Webpage(s) | https://fenix.tecnico.ulisboa.pt/downloadFile/395146439694/paper.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
