SPECIAL NOTICE
A -- Mapping Machine Learning to Physics (ML2P)
- Notice Date
- 8/8/2025 11:31:09 AM
- Notice Type
- Special Notice
- NAICS
- 541715
— Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
- Contracting Office
- DEF ADVANCED RESEARCH PROJECTS AGCY ARLINGTON VA 222032114 USA
- ZIP Code
- 222032114
- Solicitation Number
- DARPA-SN-25-101
- Response Due
- 9/5/2025 11:59:00 PM
- Archive Date
- 09/06/2025
- Point of Contact
- Solicitation Coordinator
- E-Mail Address
-
ML2P@darpa.mil
(ML2P@darpa.mil)
- Description
- Machine learning (ML) moves fast, but it needs power. More power than we have, and that�s the problem. The Department of Defense faces additional constraints with ML deployments at the edge in resource-limited battlefield environments. The ML2P program is about prioritizing power efficiency consumption right from the start. ML2P will map ML efficiency directly to physics using precise Joule measurements, enabling accurate power and performance predictions across diverse hardware architectures. ML2P will develop multi-objective optimization functions that balance power consumption with performance metrics and discover how local optimizations interact through Energy Semantics of ML (ES-ML) to solve the energy-aware ML optimization problem.
- Web Link
-
SAM.gov Permalink
(https://sam.gov/opp/c6233393d88d450ebf942f87430516fe/view)
- Record
- SN07543115-F 20250810/250808230042 (samdaily.us)
- Source
-
SAM.gov Link to This Notice
(may not be valid after Archive Date)
| FSG Index | This Issue's Index | Today's SAM Daily Index Page |