A QoS and Container-Based Approach for Energy Saving and Performance Profiling in Multi-Core Servers


Team

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.




Related Publications

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
2020-05-01EnergiesPublication funded by RECIPE H2020 (REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems)Publication funded by Compusapien (Next-gen computing systems inspired by the human brain)
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
2019-10-09Proceedings of the 2019 IFIP/IEEE 27th International Conference on Very Large Scale Integration (VLSI-SoC)Publication funded by RECIPE H2020 (REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems)Publication funded by Compusapien (Next-gen computing systems inspired by the human brain)