Search Prime Grants

2233642

Project Grant

Overview

Grant Description
SBIR Phase I: Hybrid Computing Techniques for Quantum-Inspired Ising Machines - The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from the development of a high-speed, low-power solver based on standard semiconductor technologies that can directly solve Combinatorial Optimization Problem (COP) problems.

COP problems have broad applicability across manufacturing optimization, semiconductor wire routing, logistics planning and execution, and financial portfolio management. However, COP problems are notoriously difficult or even impossible to solve via classical computers on a scale suitable for commercial application. Current state-of-the-art COP solvers need tremendous computing power, are unsuitable for edge computing, rely on undeveloped technology, or use similar algorithms to classical computers.

The goal of this project is to provide consumers with a drop-in replacement COP solver that is faster, more precise, more mobile, and more energy efficient than state-of-the-art classical computers and COP solvers.

This Small Business Innovation Research (SBIR) Phase I project seeks to develop a Complementary Metal-Oxide-Semiconductor (CMOS) based parallel Combinatorial Optimization Problem (COP) computing cluster accessible through a cloud interface. The proposed solution will directly solve COP problems, increasing the speed, precision, and power efficiency compared to classical computers or current quantum-based COP solvers. Additionally, the cluster uses all standard semiconductor technology allowing for near-term hardware manufacturing, unlike current quantum computing competitors. The device also works at room temperature, making it the only suitable edge device for directly solving COP problems.

A hybrid computing algorithm combining the custom and classical methods will parallelize the COP solving across numerous custom chips. Many custom chips will be combined into a single cluster to maximize the speed and efficiency of the hybrid algorithms. An introductory cloud service interface will be incorporated with the custom computer cluster to facilitate outside access.

The end goal of this project is to create a state-of-the-art scalable, accessible, and economical COP solver that overcomes the inherent disadvantages of quantum and classical computing.

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.
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF22551
Place of Performance
Saint Paul, Minnesota 55129-7537 United States
Geographic Scope
Single Zip Code
Related Opportunity
22-551
Analysis Notes
Amendment Since initial award the End Date has been extended from 10/31/23 to 04/30/25.
Leviosa Technologies was awarded Project Grant 2233642 worth $275,000 from in May 2023 with work to be completed primarily in Saint Paul Minnesota United States. The grant has a duration of 2 years and was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.

SBIR Details

Research Type
SBIR Phase I
Title
SBIR Phase I:Hybrid Computing Techniques for Quantum-inspired Ising Machines
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from the development of a high-speed, low-power solver based on standard semiconductor technologies that can directly solve combinatorial optimization problem (COP) problems. COP problems have broad applicability across manufacturing optimization, semiconductor wire routing, logistics planning and execution, and financial portfolio management. However, COP problems are notoriously difficult or even impossible to solve via classical computers on a scale suitable for commercial application. Current state-of-the-art COP solvers need tremendous computing power, are unsuitable for edge computing, rely on undeveloped technology, or use similar algorithms to classical computers. The goal of this project is to provide consumers with a drop-in replacement COP solver that is faster, more precise, more mobile, and more energy efficient than state-of-the-art classical computers and COP solvers. _x000D_ _x000D_ This Small Business Innovation Research (SBIR) Phase I project seeks to develop a complementary metal–oxide–semiconductor (CMOS) based parallel combinatorial optimization problem (COP) computing cluster accessible through a cloud interface. The proposed solution will directly solve COP problems, increasing the speed, precision, and power efficiency compared to classical computers or current quantum-based COP solvers. Additionally, the cluster uses all standard semiconductor technology allowing for near-term hardware manufacturing, unlike current quantum computing competitors. The device also works at room temperature, making it the only suitable edge device for directly solving COP problems. A hybrid computing algorithm combining the custom and classical methods will parallelize the COP solving across numerous custom chips. Many custom chips will be combined into a single cluster to maximize the speed and efficiency of the hybrid algorithms. An introductory cloud service interface will be incorporated with the custom computer cluster to facilitate outside access. The end goal of this project is to create a state-of-the-art scalable, accessible, and economical COP solver that overcomes the inherent disadvantages of quantum and classical computing._x000D_ _x000D_ 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.
Topic Code
CH
Solicitation Number
NSF 22-551

Status
(Complete)

Last Modified 10/17/24

Period of Performance
5/1/23
Start Date
4/30/25
End Date
100% Complete

Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
100.0% Federal Funding
0.0% Non-Federal Funding

Activity Timeline

Interactive chart of timeline of amendments to 2233642

Transaction History

Modifications to 2233642

Additional Detail

Award ID FAIN
2233642
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
C7HUS7M6TGX1
Awardee CAGE
8RSN6
Performance District
MN-02
Senators
Amy Klobuchar
Tina Smith

Budget Funding

Federal Account Budget Subfunction Object Class Total Percentage
Research and Related Activities, National Science Foundation (049-0100) General science and basic research Grants, subsidies, and contributions (41.0) $275,000 100%
Modified: 10/17/24