Collaborative Research: ASCENT: Heterogeneously Integrated Electronic Photonic AI Accelera — NSF Award to Trustees of Boston Unive
Nontechnical Description The rapid advancement of deep neural networks (DNNs) and large language models (LLMs) is transforming many facets of modern society. These AI models are trained and deployed in data centers powered by specialized hardware such as graphics processing units (GPUs), resulting in significant energy
| Award title | Collaborative Research: ASCENT: Heterogeneously Integrated Electronic Photonic AI Accelera |
|---|---|
| Award ID | 2520334 |
| Awardee | Trustees of Boston University |
| City | BOSTON |
| State | MA |
| Amount obligated | $436,708 |
| Principal investigator | Ajay Joshi |
| Program | NSF-Intel Semiconductr Partnrs, ASCENT-Address-Chalg-Eng-Teams |
| Start date | 10/01/2025 |
| Abstract | Nontechnical Description The rapid advancement of deep neural networks (DNNs) and large language models (LLMs) is transforming many facets of modern society. These AI models are trained and deployed in data centers powered by specialized hardware such as graphics processing units (GPUs), resulting in significant energy demands and raising critical concerns around sustainability and energy security. This project aims to explore the use of light for performing neural network computations, enabling |
| Source | NSF Awards |
$799/mo
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