Mapping Machine Learning to Physics (ML2P)
| Agency: | DEPT OF DEFENSE |
|---|---|
| State: | Federal |
| Type of Government: | Federal |
| FSC Category: |
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| NAICS Category: |
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| Posted Date: | Sep 23, 2025 |
| Due Date: | Dec 8, 2025 |
| Solicitation No: | DARPA-PS-25-32 |
| Original Source: | Please Login to View Page |
| Contact information: | Please Login to View Page |
| Bid Documents: | Please Login to View Page |
Description
APEX Accelerators are an official government contracting resource for small businesses. Find your local APEX Accelerator (opens in new window) for free government expertise related to contract opportunities.
APEX Accelerators are funded in part through a cooperative agreement with the Department of Defense.
The APEX Accelerators program was formerly known as the Procurement Technical Assistance Program (opens in new window) (PTAP).
- Contract Opportunity Type: Solicitation (Original)
- Original Published Date: Sep 23, 2025 12:51 pm EDT
- Original Date Offers Due: Dec 08, 2025 05:00 pm EST
- Inactive Policy: Manual
- Original Inactive Date: Jan 07, 2026
-
Initiative:
- None
- Original Set Aside:
- Product Service Code: AC12 - NATIONAL DEFENSE R&D SERVICES; DEPARTMENT OF DEFENSE - MILITARY; APPLIED RESEARCH
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NAICS Code:
- 541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
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Place of Performance:
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.
- 675 NORTH RANDOLPH STREET
- ARLINGTON , VA 222032114
- USA
- Solicitation Coordinator
- ML2P@darpa.mil
- Sep 23, 2025 12:51 pm EDTSolicitation (Original)
Related Document
| Oct 6, 2025 | [Solicitation (Updated)] Mapping Machine Learning to Physics (ML2P) |
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