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Completed STANDARD GRANT National Science Foundation (US)

SBIR Phase I: Oscillator Processing Unit - Physical Reservoir Computing on the Edge

$2.73M USD

Funder National Science Foundation (US)
Recipient Organization Lab2701 Llc
Country United States
Start Date Mar 01, 2024
End Date Feb 28, 2025
Duration 364 days
Number of Grantees 1
Roles Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2335448
Grant Description

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will result from creating the Oscillator Processing Unit (OPU), a computational processor that would be a disruptive technology for analog computing devices operating at the network edge. The edge computing device market is projected to reach $157B by 2032. Expanding on this, machine learning, especially deep neural networks (DNNs), relies on cloud infrastructure to conduct massive computation for both model training and inference, so OPUs would have beneficial security and environmental impacts since they would reduce reliance on the cloud.

The proposed OPUs could overcome the von Neumann bottleneck while also enabling a smaller form factor, increased energy efficiency, and faster speeds. As the US seeks to reduce reliance on foreign microchip manufacturers, OPUs could also provide a powerful, viable alternative that could be manufactured in the US. The technological impacts of this project would result from a more fundamental understanding of how oscillators, which are one of the most prolific dynamic systems in the universe, can also be reconsidered as physical computers.

This Small Business Innovation Research (SBIR) Phase I project seeks to leverage two types of oscillator-based neuromorphic computers. By exploring the dynamics of oscillator computers, an improved understanding of how nonlinear dynamics are translated into computational ability will be developed. Further, this is expected to provide insights into how optimal oscillator cores could be constructed for Oscillator Processing Units (OPUs).

These enhanced OPUs will converge two separate methods of analog computing: physical reservoir computers and adaptive oscillators. Ultimately, since an oscillator core’s memory and processing are not independent, OPUs could provide a solution to the von Neumann bottleneck. This work would establish a fundamental scientific understanding of the link between physics and information.

Leveraging these two disparate forms of neuromorphic intelligence will also be the basis of a powerful Oscillator Processing Unit capable of acting as both an AI inference processor and a generalized computing processor.

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.

All Grantees

Lab2701 Llc

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