Collaborative Research: ASCENT: Optimal Thermal Management for Continued Scaling of 3D Het — NSF Award to University of Washington
Recent advancements in Artificial Intelligence (AI) drive unprecedented innovation but face the critical challenge of escalating power consumption. The rapid expansion of AI leads to unsustainable energy use for computation and cooling, threatening its widespread adoption. While three-dimensional heterogeneous integrat
| Award title | Collaborative Research: ASCENT: Optimal Thermal Management for Continued Scaling of 3D Het |
|---|---|
| Award ID | 2520269 |
| Awardee | University of Washington |
| City | SEATTLE |
| State | WA |
| Amount obligated | $310,000 |
| Principal investigator | Baosen Zhang |
| Program | NSF-Intel Semiconductr Partnrs, ASCENT-Address-Chalg-Eng-Teams |
| Start date | 10/01/2025 |
| Abstract | Recent advancements in Artificial Intelligence (AI) drive unprecedented innovation but face the critical challenge of escalating power consumption. The rapid expansion of AI leads to unsustainable energy use for computation and cooling, threatening its widespread adoption. While three-dimensional heterogeneous integration offers performance and energy efficiency gains through miniaturization for data-intensive AI workloads, this miniaturization simultaneously increases power density and reduces |
| Source | NSF Awards |
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