Abstract
Application energy optimization in HPC data centers face two critical gaps. Systematic methodologies that connect data center policies to application decisions and accessible monitoring tools that enable data-driven optimization. We address both gaps through two complementary pillars. First, we present a methodology based on extended weighted Energy Delay Product (EDP) to translate data center operational priorities and integrate energy considerations into the energy optimization workflow which starts from continuous monitoring through targeted optimization. Second, we present a user-space monitoring tool, Omnistat, that enables this methodology by providing developers with direct access to actionable energy telemetry. Through deployment on the Frontier supercomputer and case studies exploring performance-energy trade-offs, we show how these pillars help energy as an integral optimization target for developers as active participants in data center efficiency.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2025 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC 2025 Workshops |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 2007-2016 |
| Number of pages | 10 |
| ISBN (Electronic) | 9798400718717 |
| DOIs | |
| State | Published - Nov 15 2025 |
| Event | 2025 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC 2025 Workshops - St. Louis, United States Duration: Nov 16 2025 → Nov 21 2025 |
Publication series
| Name | Proceedings of 2025 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC 2025 Workshops |
|---|
Conference
| Conference | 2025 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC 2025 Workshops |
|---|---|
| Country/Territory | United States |
| City | St. Louis |
| Period | 11/16/25 → 11/21/25 |
Funding
This research used resources of the OLCF at ORNL, which is supported by DOE’s Office of Science under Contract No. DE-AC05-00OR22725. We are grateful to James B. White III who provided insights that greatly assisted this work.
Keywords
- Application Optimization
- Energy Delay Product
- Energy Efficiency
- Monitoring