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.
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.
Awardee
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
Grant Program (CFDA)
Awarding Agency
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
Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
Activity Timeline
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
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