Category II: Sagebrush - An AI Inference Resource for ACCESS, NAIRR, and the Nation
- Institution
- University of Texas at Austin, TX
- Principal investigator
- Niall I Gaffney
- Funding
- $5.0M
- Duration
- 2026–2028
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Abstract
Sagebrush is a transformative generative artificial intelligence (AI) inference platform, designed to accelerate scientific discovery by providing researchers with a powerful tool for AI-driven discovery. As fields such as genomics, health care, and civil engineering require the most advanced real-time analysis, traditional GPU-based systems struggle to meet the demands for speed, scalability, and sustainability. Sagebrush addresses these challenges by leveraging cutting-edge SambaNova AI processors, which deliver unmatched performance while minimizing energy consumption. Hosted at the Texas Advanced Computing Center (TACC) - a leader in high-performance computing and home to the NSF’s Leadership Class Computing Facility (LCCF) - Sagebrush integrates seamlessly with existing NSF resources to ensure broad access for researchers across disciplines. The platform is optimized for AI inference workloads, enabling scientists to interact with large-scale AI models in real time. By offering user-friendly tools like Jupyter notebooks and web-based chatbot interfaces, the platform lowers technical barriers, empowering researchers of all backgrounds to harness AI for transformative discoveries. 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.
Research team
- Niall I GaffneyPI
- Maytal Dahan
- Joseph Stubbs
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