Planning: DCL EPSCOR: CISE Large: Hyperscale Analog Edge Computing with Brain-inspired Har — NSF Award to University of Oklahoma N
Artificial intelligence (AI) technologies are transforming nearly every sector of society, yet the hardware that powers them is rapidly approaching fundamental limits in energy efficiency and scalability. Current systems, built on traditional digital CMOS architectures, suffer from the so-called von Neumann bottleneck—
| Award title | Planning: DCL EPSCOR: CISE Large: Hyperscale Analog Edge Computing with Brain-inspired Har |
|---|---|
| Award ID | 2440153 |
| Awardee | University of Oklahoma Norman Campus |
| City | NORMAN |
| State | OK |
| Amount obligated | $198,270 |
| Principal investigator | Yaser Banad |
| Program | Information Technology Researc |
| Start date | 08/15/2025 |
| Abstract | Artificial intelligence (AI) technologies are transforming nearly every sector of society, yet the hardware that powers them is rapidly approaching fundamental limits in energy efficiency and scalability. Current systems, built on traditional digital CMOS architectures, suffer from the so-called von Neumann bottleneck—a separation of memory and processing that leads to significant energy and performance inefficiencies. As AI systems become more complex and pervasive, overcoming these limitations |
| Source | NSF Awards |
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