Abstract & Details
Description
Award ID: 2518375
This Pathways to Enable Open-Source Ecosystems (POSE) project accelerates the adoption of open-source tools to design energy-efficient artificial intelligence (AI) hardware systems. By enabling rapid prototyping and lowering the barriers to system-on-chip design, the project supports innovation across scientific domains that rely on specialized AI hardware. The solution aims to establish a sustainable ecosystem for modular, transparent, and reusable hardware design through collaboration with stakeholders and a shared vision for extensible design flows. These efforts advance semiconductor and computing innovation while expanding access to next-generation hardware design. This Pathways to Enable Open-Source Ecosystems (POSE) project scopes activities for an open-source ecosystem for customizable AI hardware generation and system-on-chip design. The projects goals are to: (1) conduct a comprehensive needs assessment via structured surveys and interviews, (2) evaluate the ecosystem through domain-specific pilot deployments, (3) analyze barriers to educational adoption, (4) design community governance models, and (5) promote contributor growth through training and mentorship. The project aims to gather actionable insights to improve usability, documentation, and onboarding, ultimately supporting greater adoption and long-term sustainability. By enabling customizable, efficient hardware generation and fostering a scalable, community-driven governance structure, the project defines a roadmap for open-source hardware tools to serve a user base across academia, education, and industry. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Florence Rabanal
This Pathways to Enable Open-Source Ecosystems (POSE) project accelerates the adoption of open-source tools to design energy-efficient artificial intelligence (AI) hardware systems. By enabling rapid prototyping and lowering the barriers to system-on-chip design, the project supports innovation across scientific domains that rely on specialized AI hardware. The solution aims to establish a sustainable ecosystem for modular, transparent, and reusable hardware design through collaboration with stakeholders and a shared vision for extensible design flows. These efforts advance semiconductor and computing innovation while expanding access to next-generation hardware design. This Pathways to Enable Open-Source Ecosystems (POSE) project scopes activities for an open-source ecosystem for customizable AI hardware generation and system-on-chip design. The projects goals are to: (1) conduct a comprehensive needs assessment via structured surveys and interviews, (2) evaluate the ecosystem through domain-specific pilot deployments, (3) analyze barriers to educational adoption, (4) design community governance models, and (5) promote contributor growth through training and mentorship. The project aims to gather actionable insights to improve usability, documentation, and onboarding, ultimately supporting greater adoption and long-term sustainability. By enabling customizable, efficient hardware generation and fostering a scalable, community-driven governance structure, the project defines a roadmap for open-source hardware tools to serve a user base across academia, education, and industry. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Florence Rabanal
| Status | Active |
|---|---|
| Effective start/end date | 08/15/25 → 07/31/27 |
Funding
- (POSE) NSF Pathways to Enable Open-Source Ecosystems: $300,000.00
Active Fiscal Year
- FY2026
- FY2025
- FY2027
Start Fiscal Year
- FY2025
TIP Programs
- (POSE) NSF Pathways to Enable Open-Source Ecosystems
Key Technology Areas
- Artificial Intelligence
- (confidence score: 96%)
- Advanced Computing and Semiconductors
- (confidence score: 100%)
Technology Foci
- Semiconductors
- (confidence score: 100%)
- Advanced Computer Software
- (confidence score: 97%)
- Advanced Computer Hardware
- (confidence score: 98%)
- Artificial Intelligence (Broad)
- (confidence score: 100%)
Congressional District at Award
- District n. 01 of Rhode Island
Current Congressional District
- District n. 01 of Rhode Island
United States
- Rhode Island
Core Based Statistical Area (CBSA)
- Providence-Warwick, RI-MA
County
- County: Providence, RI
EPSCoR Jurisdiction
- Yes
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