A QoS and Container-Based Approach for Energy Saving and Performance Profiling in Multi-Core Servers
| Atienza Alonso David |
| Zapater Sancho Marina |
Containergy is a new performance evaluation and profiling tool that uses software containers to perform application runtime assessment, providing energy and performance profiling data. It is focused on energy efficiency for next generation workloads and IT infrastructure.
Run-time profiling of software applications is key to energy efficiency. Even the most optimized hardware combined to an optimally designed software may become inefficient if operated poorly. Moreover, the diversification of modern computing platforms and broadening of their run-time configuration space make the task of optimally operating software ever more complex.
With the growing financial and environmental impact of data center operation and cloud-based applications, optimal software operation becomes increasingly more relevant to existing and next-generation workloads. In order to guide software operation towards energy savings, energy and performance data must be gathered to provide a meaningful assessment of the application behavior under different system configurations, which is not appropriately addressed in existing tools.
Containergy is a new performance evaluation and profiling tool that uses software containers to perform application run-time assessment, providing energy and performance profiling data with negligible overhead (below 2%). It is focused on energy efficiency for next generation workloads.
|Containergy-A Container-Based Energy and Performance Profiling Tool for Next Generation Workloads|
|Silva-de-Souza, Wellington; Iranfar, Arman; Braulio, Anderson; Zapater, Marina; Xavier-de-Souza, Samuel; Olcoz, Katzalin; Atienza, David|
|A QoS and Container-Based Approach for Energy Saving and Performance Profiling in Multi-Core Servers|
|de Souza, Wellington Silva; Iranfar, Arman; Silva, Anderson; Zapater, Marina; de Souza, Samuel Xavier; Olcoz, Katzalin; Atienza, David|
|2019-10-09||Proceedings of the 2019 IFIP/IEEE 27th International Conference on Very Large Scale Integration (VLSI-SoC)|