Collaborative Research: CIRC: ENS: Enabling Detailed, Open-Source Accelerator Modeling — NSF Award to University of Wisconsin-Madi
The rapid end of Moore’s Law and Dennard’s Scaling has driven computing systems, from smartphones to supercomputers, to embrace heterogeneous architectures for continued efficiency gains. As specialized, compute-intensive workloads such as machine learning become increasingly prominent, there is a critical need for acc
| Award title | Collaborative Research: CIRC: ENS: Enabling Detailed, Open-Source Accelerator Modeling |
|---|---|
| Award ID | 2450448 |
| Awardee | University of Wisconsin-Madison |
| City | MADISON |
| State | WI |
| Amount obligated | $360,000 |
| Principal investigator | Matthew Sinclair |
| Program | CCRI-CISE Cmnty Rsrch Infrstrc |
| Start date | 08/15/2025 |
| Abstract | The rapid end of Moore’s Law and Dennard’s Scaling has driven computing systems, from smartphones to supercomputers, to embrace heterogeneous architectures for continued efficiency gains. As specialized, compute-intensive workloads such as machine learning become increasingly prominent, there is a critical need for accurate, open-source simulation tools to model and evaluate the next generation of hardware accelerators. However, the pace of innovation in accelerator architectures, particularly g |
| Source | NSF Awards |
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